DialogBrain
About
Unified inbox MCP for WhatsApp, Telegram, Email, voice — read/send messages, search conversations, manage contacts, query knowledge graph, and trigger AI agents through natural language.
Details
- Author
- saloprj
- Downloads
- 393
- Categories
- Communication, Knowledge Base
Jump to
- Unified inbox covering WhatsApp, Telegram, Email, and voice.
- Read and send messages across all supported platforms.
- Search conversations across platforms.
- Manage contacts in the unified inbox.
- Query a knowledge graph using natural language.
- Trigger AI agents to perform tasks.
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
DialogBrainCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
— (No installation, configuration, or invocation details are provided in the README.)
contacts_find
👤 Search for contacts in your address book by name or username. When to use: - User asks 'find contact X' or 'who is Y?' - User wants to know someone's username or ID - Before sending a message to verify contact exists - To get contact's channel reference for messaging Examples: ❓ User: 'find contact named [name]' → contacts_search(query='[name]', limit=5) ❓ User: 'who is [full name]?' → contacts_search(query='[full name]', limit=1) ❓ User: 'search for @username' → contacts_search(query='username', limit=10) Returns: name, username, channel, channel_ref, similarity_score, match_type. Plus: - entity_id: local DB key — pass to contacts.profile. Null for live-discovered contacts (skip contacts.profile for those). - telegram_user_id (when channel='telegram'): the Telegram user ID — pass to calls.make / messages.send. NOT entity_id.
contacts_discover
Search for a contact on a live channel (Telegram, WhatsApp, etc.) before adding them. Use this to look up a person by username or phone number before calling contacts.sync.
contacts_sync
Add a discovered contact and open a conversation thread. Returns thread_id for the new conversation. Call contacts.discover first to verify the contact exists.
contacts_profile
👤 Get full profile for a contact: all channel identities, notes, role, capabilities, birthday. When to use: - After contacts.find to get complete info about a specific person - To see all channels a contact is reachable on - To read notes, role, or capabilities for a contact Requires contact_id (entity_id) from contacts.find.
contacts_update
✏️ Update a contact's profile: name, notes, role, capabilities, birthday, preferred channel. When to use: - User wants to add notes about a contact - User wants to set/update role or capabilities for a contact - User wants to rename a contact or update birthday Requires contact_id (entity_id) from contacts.find. At least one optional field must be provided.
contacts_add_channel
🔗 Link a new channel identity (email, phone, LinkedIn, etc.) to an existing contact. When to use: - User learns a contact's email or phone and wants to save it - User wants to link a LinkedIn/Instagram profile to an existing contact - Adding a second channel for an existing person Requires contact_id (entity_id) from contacts.find.
group_discovery_search
Search for public groups or channels by topic on Telegram (or other channels). Returns matching groups with title, member count, and whether messages can be previewed. When to use: - Finding groups related to a topic or niche - Building a list of groups for outreach or monitoring After searching, use group_discovery.scan to evaluate quality before joining.
group_discovery_add
Add a specific group to your discovery list by @username or invite link (t.me/...). When to use: - You already know the group's @username or invite link - Adding a known group without searching Returns: group metadata including id, title, member_count.
group_discovery_list
List groups you've found and joined in this workspace. Lifecycle values: - discovered: found but not yet evaluated - bookmarked: saved for later - monitored: joined and actively syncing messages - dismissed: hidden By default, dismissed groups are excluded. Returns: id, title, member_count, lifecycle, scan_status, overall_score.
group_discovery_preview_messages
Read recent public messages from a group without joining it. Only works for groups where can_preview_history=true. Use this to manually evaluate message quality before deciding to join. For an automated quality score, use group_discovery.scan instead. Returns: list of recent messages with sender, text, date, is_reply.
group_discovery_scan
Scan a group to evaluate its quality before joining. Fetches recent messages, analyzes activity, spam, and engagement, then returns a quality score and plain-English verdict. When to use: - After finding groups with group_discovery.search - Before deciding which groups to join Returns: overall_score (0-1), is_disqualified, disqualify_reasons, individual scores, and a verdict string.
group_discovery_join
Join a group and start syncing its messages to your inbox. The group must be in your discovery list (use group_discovery.search or group_discovery.add first). What this does: - Joins the group on Telegram (or other channel) - Creates a thread in your inbox for syncing messages - Optionally enables AI auto-reply drafts Returns: success, thread_id, auto_reply_enabled.
files_ingest
Save and index a file into the knowledge base. Use this when the user asks to save, store, or remember a document. The file will be processed (OCR if needed) and indexed for future search.
files_read
Read **text content** of an attached file. Works for: .txt, .md, .json, code files, and PDFs (after files.ingest extracts text). DO NOT call on binary files — for IMAGES use `files.get_base64`, for AUDIO/VIDEO it cannot be transcribed via this tool, and for non-PDF DOCUMENTS run `files.ingest` first, THEN files.read. Calling on a binary mime-type returns an error — saves you a turn to read the routing hint before deciding.
files_upload
Upload a file to DialogBrain and get a file_id for use in messages_send. When to use: - User wants to send a file/image to a contact - Before calling messages_send with an attachment Returns: file_id (integer) to pass to messages_send attachments parameter.
images_generate
Generates a PNG image from a text prompt using Gemini 2.5 Flash Image. Returns a file_id consumable by messages.send(attachments=[...]) and other file-aware tools. Supports up to 12 reference image file_ids for subject-consistent edits and composition (use file IDs from the [ATTACHMENTS] block, files.search, or workspace.search). Latency: ~8-10s per image. Output: 1024×1024 PNG.
videos_generate
Generate a short video (5-10s) from a text prompt using BytePlus Seedance. Optionally accepts up to 12 image file IDs from the user's attached files (visible in the [ATTACHMENTS] block) as `reference_file_ids` for style and composition. Returns immediately with a job_id; the video is delivered back via continuation when the job completes (~30-90s for fast model, ~2-5min for pro). Reference images are temporarily re-hosted on a third-party CDN (imgbb) for the duration of generation and deleted on completion — don't submit confidential references. Gated behind a workspace opt-in flag.
images_search
Searches images in this workspace by visual content using vector embeddings (Voyage multimodal-3). Pass a text description; returns ranked file_ids with cosine scores and presigned download URLs. Up to 50 results.
vision_query
Look at the screen currently being shared in a meeting and answer a question about it. Returns a natural-language answer based on the visual content. Use ONLY when the user explicitly asks about the screen/slide/document being shown.
youtube_list_videos
List videos on the connected YouTube channel. Returns id, title, published_at, view_count. Paginate via page_token.
youtube_list_comments
List comment threads on a YouTube video. Pass video_id (e.g. 'dQw4w9WgXcQ') or channel_ref ('youtube:video:<id>'). Returns top-level comments with inline replies.
youtube_post_comment_reply
Post a comment on a YouTube video, or reply to an existing comment. Pass video_id for a top-level comment, OR parent_comment_id to reply. AI-disclosure suffix appended automatically when configured.
youtube_delete_comment
Permanently delete a YouTube comment by id (or 'youtube:comment:<id>'). Cannot be undone. Costs 50 quota units.
youtube_delete_video
Permanently delete a YouTube video by id (or 'youtube:video:<id>'). Cannot be undone. Costs 50 quota units. Caller must own the channel.
youtube_moderate_comment
Apply a moderation status to a YouTube comment. Allowed status values: heldForReview, published, rejected, spam. Costs 50 quota units.
youtube_upload_video
Upload a workspace-owned video file (file_id) to the connected YouTube channel. Returns video_id + thread_id. Costs 1600 quota units. Default privacy is 'private' — pass privacy='public' to publish.
youtube_video_query
Ask Gemini about a YouTube video. Pass a video URL and any prompt — verbatim transcript with timestamps, summary, targeted Q&A about content or visuals, translation, etc. Works on any public/unlisted video.
files_info
Get metadata and download URLs for files by their IDs. When to use: - After messages_read_history returns attachment_file_ids - To get a presigned download URL to read a received file Returns: filename, mime_type, byte_size, download_url (1-hour presigned URL).
files_get_base64
Download one or more files server-side and return their content as base64-encoded strings. Use this to inspect images, PDFs, or any binary file attached to messages when you cannot access presigned S3 URLs directly. Supports up to 5 files per call, max 15 MB each. For large files batch in groups of 1-2 to avoid oversized responses.
messages_read_history
Read messages from a conversation thread. Use text_contains to find specific messages by content. Returns the most recent messages, including sender info and timestamps. Voice calls: each row carries a `meta` object with allowlisted keys (`event_type` ∈ 'call_started'|'call_ended'|null, `source` ∈ 'voice_transcript'|null, `call_id`, `speaker_display_name`, `duration_seconds`, `outcome`, `direction`) plus per-message `channel`. To find calls without scanning every row, use `calls.list_history` instead. Usage: 1. Get thread_id from threads.list first, OR 2. Use contact_name to auto-resolve thread_id Examples: - User: 'show me messages from chat with [contact]' → read_history(contact_name='[contact]', limit=10) - User: 'last 5 messages from thread 571' → read_history(thread_id=571, limit=5)
threads_list
List conversation threads with previews and metadata. Use before messages.read_history to resolve thread_id. Returns: id, title, last message, timestamp, unread count.
threads_update
✏️ Update a conversation thread: rename it, add notes/description, or move to a folder. When to use: - User wants to rename a chat or group - User wants to add notes/context about a conversation - User wants to organize threads into folders For DM threads, renaming also updates the linked contact's display name by default. Requires thread_id from threads.list.
folders_create
📁 Create a new inbox folder to organize threads. When to use: - User wants to create a folder to group related conversations - User wants to organize threads by topic, project, or contact type After creating a folder, use threads.update with folder_id to move threads into it.
folders_delete
🗑️ Delete an inbox folder. Threads inside become unfiled (not deleted). When to use: - User wants to remove a folder they no longer need - User wants to clean up their inbox organization Threads inside the folder are NOT deleted — they simply move back to the inbox.
ai_tags_list
List all personal AI tags. AI tags are automatic message filters: the system runs a lightweight classifier on every incoming message and applies matching tags to threads. This lets AI agents skip expensive full analysis on most messages — they only act on threads that match relevant tags, dramatically cutting LLM costs. When to use: - Check which auto-classification filters exist before creating one - Get tag IDs for add_to_thread / remove_from_thread - See how many threads each tag currently matches Returns all tags with thread counts (non-archived, included threads only).
ai_tags_create
Create a new AI tag (automatic message filter). AI tags are lightweight classifiers that run on every incoming message. When a message matches the tag's description/criteria, the thread is automatically labelled — so AI agents can cheaply pre-filter threads instead of running full LLM analysis on everything. Good descriptions are the key: they tell the classifier exactly when to apply this tag. When to use: - User wants to auto-classify incoming messages (e.g. bug reports, sales leads, support requests) - User wants to reduce AI agent costs by pre-filtering threads by topic or intent Tips for the description field: - Be specific: 'Messages reporting errors, crashes, or unexpected behavior in the product' - Include examples of what qualifies and what doesn't Limit: 20 active personal tags / 50 active team tags.
ai_tags_update
Update an existing personal AI tag's name, description, icon, color, or active state. When to use: - User wants to rename a tag - User wants to change a tag's icon, color, or description - User wants to enable or disable a tag Provide only the fields you want to change. At least one field is required.
ai_tags_delete
Delete a personal AI tag. All thread associations are removed automatically. When to use: - User wants to permanently remove a tag they no longer need This cannot be undone. Threads are NOT deleted — they just lose this tag.
ai_tags_add_to_thread
Apply one or more AI tags to a thread (manually). When to use: - User wants to label a conversation with one or more tags - User asks to categorize or tag a thread Provide the thread_id (integer) and an array of tag_ids to apply. If a tag is already applied it will be updated to is_manual=true.
ai_tags_remove_from_thread
Remove a specific AI tag from a thread. When to use: - User wants to un-label or remove a specific tag from a conversation - User wants to correct an incorrectly applied tag Provide both thread_id and tag_id.
ai_filters_list
List all AI filters for the current workspace. AI filters are semantic intent-based message filters that use embeddings (vector representations) to detect whether an incoming message matches a specific intent or topic. Unlike keyword filters, they understand meaning: 'I need help with my order' and 'my package hasn't arrived' both match a 'shipping support' filter even without shared keywords. Each filter stores a reference embedding of its description. When a message arrives, its embedding is compared via cosine similarity against the filter's reference vector. If the similarity exceeds the threshold, the filter matches. When to use: - Check which semantic filters already exist before creating a new one - Get filter IDs for use in trigger conditions - Review thresholds and active status of existing filters Returns all filters with id, name, description, threshold, and is_active.
ai_filters_create
Create a new AI filter for semantic intent-based message matching. AI filters use vector embeddings (via Voyage AI) to detect whether an incoming message matches a specific intent or topic. The filter's description is embedded as a reference vector at creation time. When a message arrives, its embedding is compared against this reference using cosine similarity. The description field is the most important part — it becomes the reference embedding that all incoming messages are compared against. Write it as a clear statement of what kind of messages should match: - 'Customer asking about pricing, subscription plans, or billing' - 'User reporting a bug, crash, or unexpected behavior in the product' - 'Inbound sales lead expressing interest in purchasing or trialing' The threshold controls sensitivity: 0.5 is a balanced default, lower values (0.3) cast a wider net, higher values (0.8) require closer matches. Note: This tool calls the Voyage AI embedding API to generate the reference vector.
ai_filters_update
Update an existing AI filter's name, description, threshold, or active state. When to use: - User wants to rename a filter - User wants to refine the filter description to improve match accuracy - User wants to adjust the similarity threshold (higher = stricter matching) - User wants to enable or disable a filter without deleting it Provide only the fields you want to change. At least one field is required. Note: If the description is changed, this tool calls the Voyage AI embedding API to re-generate the reference vector with the new description text.
ai_filters_delete
Permanently delete an AI filter. When to use: - User wants to remove a filter they no longer need This action cannot be undone. Any triggers that reference this filter by ID will no longer match it — review and update those triggers after deletion.
ai_filters_test
Test a message against an AI filter to check whether it would match. This tool embeds the provided message using Voyage AI and computes the cosine similarity between the message vector and the filter's stored reference vector. It returns the similarity score, whether the message would match (similarity >= threshold), and the filter's threshold value. Use this to: - Verify a filter works as intended before using it in a trigger - Tune the threshold by testing borderline messages - Debug why a message did or did not match a filter in production Returns: {similarity: float, matched: bool, threshold: float} Note: This tool calls the Voyage AI embedding API to embed the test message.
messages_send
Send a message to a thread, channel, or contact. Supports Telegram, Email, LinkedIn, and other connected channels. For LinkedIn posts (comment_thread kind), this posts a comment on the post. Can automatically resolve recipients and channels when not specified. Can send files/images/documents as attachments — pass `attachments=[file_id, ...]` with integer file IDs obtained from collections.list_files, workspace.search, or files.search. `text` is optional when attachments are provided.
messages_delete
Delete a message from a thread. Supports Telegram, WhatsApp, and other connected channels. Note: Some channels have time limits on message deletion.
messages_forward
Forward a message from one thread to another. Supports native Telegram forwarding (preserves original sender attribution) and text-based forwarding for cross-channel scenarios.
knowledge_query
Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use workspace.search for that.
kg_find_entity
Find an entity by name in the Knowledge Graph. USE WHEN user mentions a person, project, company by name and you need: - To resolve a name to entity_id for subsequent queries - 'Кто работает над X?' → find X first - 'Расскажи про Y' → find Y first RETURNS entity_id for use in kg.get_relationships or kg.explore. ALWAYS use this as the FIRST step in KG query chains.
kg_get_relationships
Get relationships for a specific entity from Knowledge Graph. USE WHEN: - 'Кто работает над X?' - filter by works_on - 'С кем общался Y?' - filter by discussed_with - 'Кто из компании Z?' - filter by member_of - 'Что связано с W?' - no filter, get all REQUIRES: entity_id from previous kg.find_entity step. Use: {{step_N.entity_id}} where N is the find_entity step number.
calendar_create_event
Create a new event in Google Calendar. Specify the title, start time, end time, and optionally invite attendees. Use ISO 8601 format for dates (e.g., 2024-12-15T14:00:00).
calendar_list_events
List events from Google Calendar. Shows upcoming events by default. Can filter by date range and search query.
calendar_update_event
Update an existing event in Google Calendar. Can modify title, time, location, description, and attendees. Only specified fields will be updated.
calendar_delete_event
Delete an event from Google Calendar. This action cannot be undone. Use with caution.
calendar_check_availability
Check when you have free time in Google Calendar. Shows busy periods and free slots in a given time range. Useful for finding meeting times or checking schedule conflicts.
web_search
Search the web for current information, news, facts, prices, or events. Use this when the user asks about something that requires up-to-date information from the internet, or when internal knowledge base doesn't have the answer. Examples: recent news, stock prices, weather, product information, current events.
web_fetch
Fetches a single URL and returns its content. Use this when you have a specific URL in mind — for example, after web.search returns a link you want to read, or when the user pastes a URL. Modes (extract): - 'auto' (default): picks the right mode based on response content type. - 'markdown': for HTML pages; returns cleaned markdown plus the page <title>. - 'text': for JSON/XML/plaintext APIs; returns the raw decoded body. - 'file': for images, PDFs, audio, video, archives, or any binary — ingests the bytes into the user's file storage and returns a file_id you can pass to messages.send (to send as an attachment), agents.add_file (to add to agent knowledge), or files.read. Use web.fetch (not files.upload) when you need the file_id immediately for the next tool call — files.upload(source_url=…) is async and won't have the file ready in the same turn. Use web.search (not web.fetch) when you don't have a specific URL yet and need to find one.
web__local_search
Multi-source web research with citations. Returns a synthesized answer with numbered [^1] markers and a citations array of {url, title, snippet, index}. Use for evidence-backed synthesis (competitive analysis, regulatory summary, whitepaper section). For quick fact lookups use web.search instead.
documents_create
Generate a document (PDF / PPTX / DOCX / HTML) from markdown content authored by you. REQUIRED parameters: - title: Short human-readable title. - content_markdown: The body. Slides separated by `---` on its own line at the top level (Marp rule). Tables, code, lists, footnotes, definition lists, and {.section-header} class attrs all parse. - format: "document" (single flowing body) or "presentation" (slides). - output_type: "pdf", "pptx", "docx", or "html". Optional: - theme: "default" | "corporate" | "minimal" | "pitch" | "invoice" | "contract" | "cinema" | "editorial" (default "default"). cinema/editorial are presentation-only (engine=marp). - language: BCP-47 tag (default "en"). Drives font fallback for Cyrillic/CJK/Arabic content. - engine: "marp" | "weasyprint". For format=presentation PDF/HTML only. Default "marp" (designer-grade Chromium renderer with full CSS3, web layout, and {.cover}/{.hero}/{.split}/{.stats}/{.dark} layout classes). Pass "weasyprint" for the legacy print-CSS path. Rejected for format=document or output_type=pptx. DELIVERY CONTRACT (CRITICAL): After this tool returns a `file_id`, deliver the file by calling `messages.send(attachments=[file_id], text="<short caption>")`. Do NOT embed the file_id in a markdown link, a `sandbox:` URL, or `/api/files/<id>/download` text — those render as plain text on the recipient's channel, not as a file attachment. The `attachments` parameter is the ONLY way the file actually attaches. CONVENTIONS: - Two-column slide: wrap with `::: cols\n::: col\n…\n:::\n::: col\n…\n:::\n:::`. - Speaker notes (presentations only): `::: notes\n…\n:::` at the end of a slide block. NOT `<!-- ... -->` (comments are escaped, not captured). - Section header slide: `{.section-header}` on its own line directly above the heading. Block-attr form, not inline. - Images: only `` (workspace file_id), `data:image/...` URIs, or hosts in DOCUMENTS_MEDIA_URL_ALLOWLIST. Other URLs are dropped with `[image removed]`. LAYOUT CLASSES (engine=marp only — ignored under engine=weasyprint): - `{.cover}` — title-slide layout (centered headings, gradient background). - `{.hero image="file:NNN"}` — full-bleed background image with dark overlay and white headline. - `{.split image="file:NNN"}` — 50/50 image left, content (heading/bullets) right. - `{.stats}` — 3-up KPI cards: each card is `### big-number` followed by a one-line label paragraph. - `{.dark}` / `{.invert}` — per-slide dark mode override. Both `image="file:NNN"` and `image=file:NNN` are accepted (quoted or unquoted). Place the class line on its own row directly above the slide content. Format × output_type rules: - `document` + `pptx` is rejected — set `format=presentation` or pick pdf/docx/html. - `theme=invoice/contract` + `output_type=pptx` silently uses the default PPTX master. For theme="invoice", every invoice MUST include a "Total" row whose value equals sum(line items) + tax (within ±0.01). The renderer fails closed on missing or mismatched totals. EXEMPLAR — invoice (English): # Invoice INV-{YYYYMMDD-HHMMSS} **From:** {Issuer Legal Name}, {Address}, {Tax ID} **To:** {Customer Name}, {Customer Address}, {Customer Tax ID} **Issue date:** {YYYY-MM-DD} **Due date:** {YYYY-MM-DD} | Description | Qty | Unit price | Total | |---|---:|---:|---:| | {Service 1} | 1 | 1500.00 | 1500.00 | | {Service 2} | 2 | 500.00 | 1000.00 | **Subtotal:** USD 2500.00 **Tax (20%):** USD 500.00 **Total:** USD 3000.00 **Payment:** {bank details OR crypto wallet — never both} EXEMPLAR — invoice (Russian): # Счёт-фактура № INV-{YYYYMMDD-HHMMSS} **От:** {Юридическое название организации}, {Адрес}, ИНН {Tax ID} **Кому:** {Название клиента}, {Адрес клиента}, ИНН {Tax ID} **Дата:** {YYYY-MM-DD} **Срок оплаты:** {YYYY-MM-DD} | Описание | Кол-во | Цена | Сумма | |---|---:|---:|---:| | {Услуга 1} | 1 | 1500.00 | 1500.00 | | {Услуга 2} | 2 | 500.00 | 1000.00 | **Подытог:** USD 2500.00 **НДС (20%):** USD 500.00 **Итого:** USD 3000.00 **Реквизиты:** {банковские реквизиты ИЛИ криптокошелёк — не оба сразу} EXEMPLAR — contract (English): # Service Agreement **Between:** {Provider Legal Name}, {Address} ("Provider") **And:** {Client Legal Name}, {Address} ("Client") **Effective date:** {YYYY-MM-DD} ## 1. Scope of services {Concise description of what Provider agrees to deliver.} ## 2. Term This Agreement begins on the Effective date and continues until {termination condition or end date}. ## 3. Compensation Client pays Provider {amount and currency} according to {payment schedule}. ## 4. Confidentiality Both parties agree to keep proprietary information of the other party confidential during and after the term of this Agreement. ## 5. Termination Either party may terminate with {N} days' written notice. ## 6. Governing law {Jurisdiction}. --- **Provider:** ____________________ **Client:** ____________________ {Provider signatory name} {Client signatory name} EXEMPLAR — contract (Russian): # Договор оказания услуг **Между:** {Юридическое название Исполнителя}, {Адрес} ("Исполнитель") **И:** {Юридическое название Заказчика}, {Адрес} ("Заказчик") **Дата вступления в силу:** {YYYY-MM-DD} ## 1. Предмет договора {Краткое описание услуг, которые Исполнитель обязуется оказать.} ## 2. Срок действия Договор вступает в силу с указанной даты и действует до {условие прекращения или дата окончания}. ## 3. Стоимость и порядок оплаты Заказчик оплачивает услуги Исполнителя в размере {сумма и валюта} в порядке {график платежей}. ## 4. Конфиденциальность Стороны обязуются сохранять конфиденциальность сведений, полученных в ходе исполнения настоящего Договора, в течение срока его действия и после его прекращения. ## 5. Расторжение Любая из сторон вправе расторгнуть Договор, направив письменное уведомление не менее чем за {N} дней. ## 6. Применимое право {Юрисдикция}. --- **Исполнитель:** ____________________ **Заказчик:** ____________________ {ФИО подписанта Исполнителя} {ФИО подписанта Заказчика}
agents_list
List all AI agents configured in the workspace. Returns agents with their basic info, trigger count, and knowledge collection count. Use this to: - See all configured AI agents - Filter by enabled/disabled status - Get agent IDs for further operations
agents_get
Get detailed information about a specific AI agent. Returns full agent config including: - Execution configuration - Tool configuration - Knowledge configuration - Escalation configuration - Triggers list - Knowledge collections - Custom AI instructions (prompt_text) - Auto-reply rules override (auto_reply_rules)
agents_create
Create a new AI agent in the workspace. Execution modes: - ai_assisted (default, recommended): Two-phase AI — fast pre-classifier (Haiku) for keyword filtering and simple replies, then full AI with tools for complex messages. Best for: auto-replies, group monitoring, keyword-based filtering. - agentic: Autonomous multi-step agent with planning and tool execution. Best for: complex scheduled tasks, multi-step automation. - rule_based: Simple pattern matching without AI. For keyword filtering: use ai_assisted mode + set keywords in trigger conditions (free, deterministic) and/or auto_reply_rules (smart, LLM-based) via agents.update.
agents_update
Update an existing AI agent's configuration. All parameters are optional — only provided fields will be updated. Use this to: - Enable or disable an agent - Change agent name or description - Assign or detach a prompt - Change default send mode - Replace knowledge collections - Update agent status - Change agent priority for trigger matching (lower number = higher priority) - Override which tools the agent can/can't call on triggered runs - Override which context sections (situation, communication style, job state, conversation history, thread summary) the agent receives - Opt into boilerplate prompt sections (safety guidelines, data confidentiality, factual accuracy) — all default OFF
agents_delete
Permanently delete an AI agent. WARNING: This cannot be undone. The agent and all its triggers will be removed.
agents_ask
Send a message to an AI agent and get its response. The agent runs with its configured prompt, tools, and knowledge. Use this to test agents or have them process a task. Returns: {status: 'replied'|'silent', response_text, messages[], full_reply, model_used, tokens_*, send_mode, execution_mode}. `messages[]` carries each messages.send invocation the agent made (text, subject, reply_to_message_id, timestamp, message_id, attachments=[{file_id,name,mime}]). `full_reply` concatenates text only — attachment-only sends show up in `messages` but not `full_reply`. `status='silent'` iff both response_text is empty AND messages is empty. Execution may take 10-60s depending on agent complexity.
agents_trigger_create
Create a new trigger for an AI agent. Triggers determine when the agent activates. Trigger types: - incoming_message: Activates on new incoming messages - schedule: Activates on a schedule - webhook: Activates on webhook events - event: Activates on system events
agents_trigger_update
Update an existing AI agent trigger. All parameters are optional — only provided fields will be updated.
agents_trigger_delete
Delete a trigger from an AI agent. WARNING: This cannot be undone.
agents_list_drafts
List pending agent drafts awaiting approval. Shows drafts that have been generated by AI agents but not yet sent. Each draft includes: - Thread/conversation info - Trigger message (what prompted the reply) - Generated response text - Creation time and expiration Use this when user asks: - 'Show pending agent drafts' - 'What messages are waiting for approval?' - 'List drafts to approve'
agents_approve_draft
Approve a pending agent draft and send the message. The draft will be sent to the conversation it was generated for. You can optionally edit the text before sending. Use this when user says: - 'Approve this draft' - 'Send this reply' - 'Approve and send' - 'Looks good, send it' IMPORTANT: This will send a message to a real person.
agents_reject_draft
Reject a pending agent draft without sending. The draft will be marked as rejected and won't be sent. Use this when the generated response isn't appropriate. Use this when user says: - 'Reject this draft' - 'Don't send this' - 'Cancel this reply' - 'Delete this draft' - 'This response is wrong'
agents_list_files
List files directly attached to this agent (agent-specific files, not shared collections). Returns file_id, title, status, and chunk_count for each file. chunk_count shows how many indexed chunks were created — 0 means the file is still processing. Use agents.add_file to attach a new file, or agents.remove_file to detach one.
agents_add_file
Attach a file to this agent's private knowledge (agent-specific files, not shared with other agents). Workflow: 1. Upload the file with files_upload (pass source_url for remote files) 2. Index it with files_ingest (pass the file_id) 3. Call this tool with agent_id + file_id Returns chunk_count — shows 0 while still processing. Call agents.list_files later to see the final chunk count once indexing completes.
agents_remove_file
Remove a file from this agent's private knowledge. The file itself is not deleted — it's just detached from this agent. Use agents.list_files to find the file_id to remove.
agents_task_complete
Report that a Claude Code agent task has been completed. Call this when you finish processing an agent_task from DialogBrain.
agent_handoff
Delegate a multi-step task (research, composing messages, booking, scheduling) to the full agentic planner. Use when a user ask needs more than a direct answer. Returns `final_answer` for you to narrate in one short sentence. Do NOT re-trigger the same handoff if the tool_result has status `timeout` or `error` — acknowledge and offer to retry.
agent_silence
End this turn without sending any message. Use when the thread is owned by a human operator after job.escalate, when the guest is self-resolving, when the message is a duplicate, or for observation-only turns. Calling this tool is the ONLY correct way to stay silent — narrated silence text (e.g. '*(Staying silent…)*', 'Internal:…') would be delivered to the guest verbatim.
agents_traces_list
List recent execution traces for an agent — the same data as /admin/requests, scoped to one agent and readable by an LLM. Use this when an agent call timed out, drafted the wrong response, or you want to know which tool/LLM call burned the latency. Pair with `agents.trace_get` for full detail on a specific trace. Filters: `status`, `success`, `source` (single value or comma-separated: `agent,voice`), `date_from`/`date_to` (ISO-8601), pagination via `limit`/`offset`. Returns `returned_count`, `dropped_on_page` (should be 0 — positive means the backend agent_id predicate let something through), and `has_more`. Edge case: a raw page of all-dedup-dropped rows yields `returned_count=0, has_more=true`; re-call with `offset += limit`.
agents_trace_get
Fetch the full execution detail for a single trace — tool executions, events timeline, LLM call spans (with error_message on failures). Use after `agents.traces_list` identifies a specific trace of interest (failed run, slow run, unexpected outcome). By default LLM `system_prompt` and `prompt_messages` are stripped — set `include_llm_bodies=true` to fetch them when diagnosing prompt engineering issues (emits a WARNING audit log). Set `full=true` to disable all field truncation. `completion_text` on failed LLM calls is always returned (capped at 8 KB).
agents_traces_stats
Aggregated trace statistics for one agent over the last N days — total runs, success rate, avg duration, error breakdown, top tools used, runs-per-day histogram. Use this when you want a bird's-eye view of an agent's health before diving into individual traces with `agents.traces_list` / `agents.trace_get`. Scoped to the target agent (exact match, no substring bleed). `days` is capped at 30 — matches the ClickHouse request_traces TTL.
agents_prompt_history
List past versions of an agent's `prompt_text`. Every edit to the agent's prompt is snapshotted to an append-only table — use this tool to browse history, find a prior known-good version, and copy it into `agents.prompt_restore`.
agents_prompt_restore
Restore a past version of an agent's `prompt_text` by version_number. Creates a new version pointing at the restored content — history is preserved. Use `agents.prompt_history` first to find the version_number you want.
agents_simulate_inbound
Replay an inbound message on a thread through the real trigger pipeline and return what would have happened. The router auto-picks the winning enabled agent + trigger by priority/specificity (same logic as production). By default send_mode='draft' so no real message is sent; pass send_mode='auto' on a test account to let the matched agent actually deliver (drafts get overwritten by the next draft, so 'auto' is the only way to verify Telegram/email delivery end-to-end). Use to verify routing for a thread: which agent answers, which trigger wins, or — when nothing matches — the structured skip reason. Pass blockchain_tx_data instead of message_text to simulate a blockchain:transfer event on the thread. Returns: {matched: true, matched_agent: {id, name, execution_mode}, matched_trigger: {id, trigger_type, conditions, specificity_score}, routing_reason, response_text, messages[], execution_mode, send_mode, model_used, tokens_input, tokens_output, latency_ms, rag_queries_made, rag_results_used} on a hit, or {matched: false, skip_reason, simulator_warnings} on a miss.
collections_list
List all knowledge collections in the workspace. Collections are named groups of files used for RAG search. Auto-created collections (per-agent, per-prompt) are hidden by default.
collections_create
Create a named knowledge collection. Collections group files for RAG search. After creating, add files with collections.add_file and assign to agents with collections.assign_agent.
collections_delete
Delete a knowledge collection. If the collection is assigned to agents, prompts, or channels, pass force=true to delete anyway. CASCADE removes all assignments automatically.
collections_add_file
Add a file to a knowledge collection. The file must be uploaded and indexed first (files_upload + files_ingest). If the file was previously removed, it is re-enabled.
collections_remove_file
Remove a file from a knowledge collection. The file itself is not deleted — only the collection membership is removed.
collections_list_files
List all files in a knowledge collection with their indexing status and chunk counts. Each returned file has a `file_id` (integer) that can be passed to messages.send as `attachments=[file_id]` to send the file to a contact, or to files.read to read its text content.
collections_assign_agent
Assign a knowledge collection to an AI agent. Once assigned, the agent's knowledge.query will automatically scope RAG search to files in its assigned collections.
collections_unassign_agent
Remove a knowledge collection from an AI agent. The collection and its files are not deleted — only the agent assignment is removed.
prompts_list
List all prompt templates in this workspace. Returns id + name + description + category so you know which prompt_id to use in prompts.get or prompts.update.
prompts_get
Get full content of a prompt template: system instructions (prompt_text) and auto-reply rules. Run prompts.list first to find the prompt_id.
prompts_update
Update a prompt template's name, system instructions, or auto-reply rules. Changes affect every agent using this template, unless the agent has its own override (set via agents.update → prompt_text). All parameters except prompt_id are optional — only provided fields are updated.
prompts_prompt_history
List past versions of a prompt template's `prompt_text`. Every edit is snapshotted to an append-only table — use this to browse history and find a version_number for `prompts.prompt_restore`.
prompts_prompt_restore
Restore a past version of a prompt template by version_number. Creates a new version pointing at the restored content — history is preserved. Fans out to every agent using this template without a per-agent override; the response includes `affected_agents` as a receipt of the fan-out.
widgets_list
List all livechat widgets. Returns widgets with their configuration, embed code, and status. Use this when user wants to see their widgets or chat widgets.
widgets_create
Create a new livechat widget for your website. The widget will be created with default settings. You can customize theme, auto-reply mode, and more. Use this when user wants to add a chat widget to their site.
widgets_update
Update an existing livechat widget configuration. You can change name, theme, auto-reply mode, and other settings. Only provided fields will be updated. Use this when user wants to modify their chat widget settings.
widgets_delete
Delete a livechat widget permanently. This will remove the widget and its embed code will stop working. Existing chat history will be preserved. Use this when user wants to remove a chat widget.
widgets_get_embed_code
Get the embed code snippet for a livechat widget. Returns HTML/JavaScript code to add to your website. The code should be placed before the closing </body> tag. Use this when user wants to install the chat widget on their site.
widgets_get
Get full configuration of a single livechat widget. Returns all settings including theme, identification, actions, and more. Use this when user wants to see or verify a specific widget's settings.
linkedin_search
Search LinkedIn for people, companies, jobs, or posts. Supports filtering by keywords, location, industry, network distance, and more. Use linkedin.search_filters first to resolve filter keywords to LinkedIn parameter IDs.
linkedin_search_filters
Get LinkedIn search filter parameter IDs. LinkedIn uses internal IDs instead of text for search filters (location, industry, etc.). Call this before linkedin.search to resolve filter keywords to their LinkedIn parameter IDs.
linkedin_get_profile
Get a LinkedIn user profile by ID, public identifier (vanity name), or profile URL. Returns name, headline, location, and other profile information.
linkedin_get_company
Get a LinkedIn company profile by company ID or vanity name. Returns company name, description, industry, size, and other details.
linkedin_update_profile
Update the authenticated user's own LinkedIn profile. Supports adding/editing experience entries (role, company, skills, dates). Also supports updating location. Headline, summary, education are NOT supported by the API.
linkedin_invite
Send a connection invitation to a LinkedIn user. Optionally include a personalized message (max 300 characters). Rate limited: LinkedIn allows 80-100 invitations per day, max 200 per week.
linkedin_list_connections
List your LinkedIn connections, sorted by most recently added.
linkedin_list_invitations_sent
List your pending sent connection invitations on LinkedIn.
linkedin_list_reactions
List all reactions (likes, celebrates, etc.) on a specific LinkedIn post.
linkedin_add_comment
Add a comment to a LinkedIn post. Use post_id from search results or thread data.
linkedin_raw_request
Send an arbitrary LinkedIn API request via Unipile's magic route. Only GET and POST methods are allowed. WARNING: This bypasses structured rate limiting and can perform destructive actions. Use this only when no other LinkedIn tool covers the needed functionality.
workspace_search
Universal workspace search: files, links, threads, messages. Runs scopes in parallel and returns sectioned results. Default scope='auto' detects target from query. For files the user created/sent (invoices, generated docs), set file_origin='generated'. Use this for all workspace search; lower-level tools are internal.
workspace_list
List every workspace the caller is a member of, with `is_current` marking the workspace this MCP key is currently routed to. Pair with `workspace.switch` to change the active workspace without reconnecting.
workspace_current
Return the workspace this MCP API key is currently routed to, with the caller's role inside it. Use this to confirm context before/after `workspace.switch`.
workspace_switch
Re-point the active MCP API key to a different workspace. Pass exactly one of `workspace_id` or `slug` (find them via `workspace.list`). Takes effect on the very next tool call — no MCP reconnect, no new API key. Sequential checkpoint: do not parallelize tool calls across a switch — calls already in flight when the switch commits will run against the previous workspace.
job_read_context
Read the current job context. Returns the full state of your active job including assignments, escalations, and any data you previously stored.
job_update_context
Update the job context by merging new data. Existing keys are preserved unless explicitly overwritten. Use this to record progress, update assignment statuses, or store intermediate results.
job_complete
Mark the job as completed. This sanitizes PII from the context and records a completion summary. Use when all tasks in the job are done.
job_escalate
Escalate the job to a human. Use when you cannot resolve an issue, someone is not responding, or a situation requires human judgment.
notes_save
Save a fact or note into the agent's memory. Use scope to choose visibility: 'workspace' = visible to every agent in this workspace (use for shared facts, project conventions); 'agent' = private to this agent (use for personal working notes); 'thread' = scoped to one conversation (use for thread-specific reminders); 'person' = scoped to one contact (use for per-contact context). If a note with the same key+scope exists it will be updated. Do NOT use this tool for behavioral rules or corrections — use feedback.save for those.
notes_recall
Recall notes from your notebook. By default returns only your own notes (all scopes, newest first). Pass filter_agent_id=<int> to read another agent's notebook, or filter_agent_id="all" (or "*") to read across every agent in the workspace. Pass scope to narrow to global/thread/person. Each result includes agent_id and agent_name of the author.
notes_search
Full-text search in your notebook. By default searches only your own notes. Pass filter_agent_id=<int> to search another agent's notebook, or "all" (or "*") for workspace-wide. Or list all notes for a person/thread by scope_ref_id.
notes_delete
Delete a note by ID from the target notebook. Same identity rules as notes.save — agents can only delete from their own notebook.
feedback_save
Save a behavioral rule, preference, or correction that should guide future agent behavior. Use this when the user gives explicit guidance like 'always reply in Russian', 'don't suggest meetings before 11am', or 'invoice link goes via email, not chat'. Structure the rule as: the rule itself, why it matters (if stated), and how to apply it. Scope: 'workspace' for org-wide rules, 'agent' for per-agent overrides, 'person' for per-contact preferences. Prefer feedback.save over notes.save for anything that's instructive rather than informational.
tasks_create
Create a new task in your to-do list.
tasks_update
Update an existing task. Set status='done' to complete it, 'cancelled' to cancel. Use summary for completion notes.
tasks_list
List your tasks, or another agent's tasks (read-only) using from_agent_id. Use filters to narrow results.
tasks_delete
Delete a task from your to-do list by its ID.
reminder_set
Schedule a reminder. One-time reminders fire at a specific datetime. Recurring reminders fire on a schedule (daily, weekly, every N days, or every N minutes). Optionally scope to a thread or target another agent.
reminder_list
List your active reminders (both one-time and recurring).
reminder_cancel
Cancel an active reminder by its trigger ID.
system_sleep
Pause execution for a given number of seconds (max 30). Use when you need to wait for an external process to complete before retrying — e.g. message sync, backfill, or API propagation. Total sleep per run is capped at 60 seconds.
calls_make
Place an outbound AUDIO/VOICE phone call via Twilio (PSTN) or Telegram (MTProto 1:1 call). Use this any time the user asks to 'call', 'ring', 'phone', 'dial', or have a spoken conversation. Do NOT use messages.send when the user asks to call someone — a call is real-time voice, not a text message. You conduct the conversation as the voice agent using the provided greeting and instructions.
calls_send_to_meet
Dispatch a workspace AI agent into an active Google Meet call. The agent joins as a participant — it can hear the conversation, respond via TTS, see the shared screen (when vision is enabled on the agent), and answer questions about what's on screen. Use when the operator wants to delegate live meeting attendance to an agent (notes, Q&A, summarization, real-time support). The Meet URL must be in canonical 3-4-3 form, e.g. https://meet.google.com/abc-defg-hij. Lookup-redirect URLs are not supported — operator must use the share-link form.
calls_send_to_telegram_call
Dispatch a workspace AI agent into an active Telegram group call (t.me/call/<slug> link). The agent joins as a participant via the workspace's Telegram account — it can hear the conversation, respond via TTS, see shared screens (when vision is enabled), and answer questions about what's on screen. Use when the operator wants to delegate live group-call attendance to an agent (notes, Q&A, summarization, real-time support). Pass either the full https://t.me/call/<slug> URL or the bare slug token.
calls_list_active
List active voice calls in this workspace. Use before calls.make on a Telegram account (only one MTProto call per account at a time) to check whether the line is free.
calls_get_transcript
Get the structured transcript and final state of a voice call by call_id. Returns per-turn rows in chronological order, call status (active/completed/failed/abandoned), duration, and an `outcome` field telling whether the recipient picked up (answered/no_answer/busy/declined/failed/unknown). `answered_at` is non-null once the recipient picked up. Returns active turns if the call is still in progress.
calls_list_history
Search historical voice calls in this workspace by participant name, contact_id, thread, channel, source, and/or date range. Returns one row per call (NOT per turn) with call_id, duration_seconds, outcome, direction, started_at, source, channel_label, and parent_thread_id (the originating chat thread for Telegram-group / Twilio-outbound / Meet calls). Pair with calls.get_transcript(call_id) for the full per-turn transcript. Use this instead of messages.read_history for cross-thread call queries — group calls and Meet sessions live on per-call sub-threads, not on the parent chat thread.
calls_wait
Block until a voice call ends (status changes from 'active') or timeout elapses. Returns ended=true with final state when the call has ended; ended=false on timeout (re-issue to keep waiting). The returned state includes `outcome` so callers can branch on pickup vs. no-answer (answered/no_answer/busy/declined/failed/unknown). Default timeout 90s; cap 110s — bounded by nginx proxy_read_timeout 120s on /mcp.
calls_hangup
Hang up an active voice call by call_id. Use after calls.make when the agent decides to terminate before the callee does, or to abort a stuck call. Idempotent: returns success if the call is already terminal.
browser_open
Open a URL in a remote browser. Optional identity_name attaches the workspace's saved login cookies first.
browser_snapshot
Return a YAML aria_snapshot of the page DOM. Truncated at 32KB. Use the snapshot to find element `ref`s for browser.click / browser.fill.
browser_click
Click an element. `ref` is a CSS selector (e.g., 'button.submit').
browser_fill
Fill an input or textarea with the given value. `ref` is a CSS selector (e.g., 'input[name=email]').
browser_wait_for
Wait for a selector to appear OR a navigation URL to match a glob pattern. Provide `ref` (selector) OR `url_pattern` (glob).
browser_attach_identity
Switch the page's identity by loading saved cookies + storage. Use only when switching identity mid-page; for first navigation, pass `identity_name` to browser.open instead.
browser_close
Close a page opened by browser.open.
browser_hover
Hover the mouse over an element (reveals tooltips + hover menus). `ref` is a CSS selector.
browser_select_option
Pick option(s) in a native <select> dropdown. Pass `value` (matches the option's value attr) OR `label` (matches its visible text). Lists allowed for multi-select.
browser_press_key
Press a keyboard key (e.g., 'Enter', 'Tab', 'Escape', 'ArrowDown') or a single character. Optional `ref` selector focuses an element first.
browser_navigate_back
Navigate back in the page's history (browser back button). Returns the new URL + title.
browser_take_screenshot
Capture a PNG screenshot of the page or a specific element. Returns base64-encoded image bytes. Use sparingly — favor browser.snapshot for structured DOM understanding.
browser_tabs
Manage tabs within the same BrowserContext as `page_id`. `action` ∈ {list, switch, close, new}. For list, returns all open tab metadata; for new, returns the new tab's page_id.
browser_evaluate
Run JavaScript in the page context and return the result. Use for state not in the a11y tree, captcha iframe inspection, DOM events. Expression can be a value (e.g., 'document.title') or an arrow function ((arg) => ...) — pass arg via the `arg` parameter. Result is JSON-serialized; non-serializable values become strings. 256KB cap on output.
browser_drag
Drag one element onto another. `source_ref` is the element to grab; `target_ref` is where to drop. Both are CSS selectors. Used for slider captchas, kanban, drag-and-drop uploads.
browser_type
Type text into an element with per-keystroke delay (organic). Each character dispatches keydown/keypress/keyup, unlike browser.fill which replaces .value instantly. Use when the page listens to keystroke events or for typing-speed fingerprint checks. `delay_ms` defaults to 50.
browser_fill_form
Fill multiple form fields in one call. `fields` is a list of {ref, value} dicts. ref is a CSS selector; value is a string (text) or boolean (checkbox). Saves N round-trips vs calling browser.fill repeatedly.
browser_resize
Resize the page viewport. Useful when a site serves different HTML based on viewport width (mobile vs desktop) or when an anti-bot scores risk by viewport dimensions.
browser_file_upload
Attach files to an <input type=file>. Pass either `local_paths` (absolute host paths) or `data` (list of {name, mime, base64} blobs written to /tmp). 25MB cap per file.
browser_handle_dialog
Respond to a pending JS dialog (alert/confirm/prompt). Pass accept=true for OK or false for Cancel. For prompt() dialogs also pass prompt_text. Dialogs are queued at page-open time; returns {pending: false} if none is waiting.
browser_console_messages
Return console.log/warn/error events captured since the last drain. Filter by level ('log'|'info'|'warning'|'error'|'debug') and/or pattern (regex). Buffer caps at 500 entries; oldest are dropped first. Set clear=false to peek without draining.
browser_network_requests
List HTTP requests the page made since open or last drain. Optional filters: method (GET/POST/...), url_pattern (regex), status_min (e.g. 400 for errors). Captures up to 200 most recent requests per page.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"dialogbrain": {
"dialogbrain": {
"url": "https://api.dialogbrain.com/mcp",
"transport": "streamable-http",
"auth": "oauth2"
}
}
}
}McpServers
{
"dialogbrain": {
"url": "https://api.dialogbrain.com/mcp",
"transport": "streamable-http",
"auth": "oauth2"
}
}Unified inbox MCP for WhatsApp, Telegram, Email, voice — read/send messages, search conversations, manage contacts, query knowledge graph, and trigger AI agents through natural language.
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