ContextPulse
About
Local-first ambient context for AI agents -- screen capture, OCR, voice transcription (Whisper), keyboard/mouse tracking, clipboard history, and semantic memory.
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Setup
Install ContextPulse in your MCP client (Claude Desktop, Cursor, Windsurf, and others).
Repository: https://github.com/contextpulse/contextpulse
Follow the installation instructions in the repository README, then restart your MCP client.
Local-first ambient context for AI agents.
Screen capture, voice dictation, clipboard, keyboard/mouse activity. All local, all private.
Developer Preview (v0.1-alpha).ContextPulse is under active development. APIs and configuration may change between releases.Report issues.
ContextPulse is a desktop daemon that captures your screen, voice, and keyboard/mouse activity in real time, then delivers it to AI agents through theModel Context Protocol (MCP). One process, one tray icon, 35 MCP tools, zero cloud dependency.
Everything stays local. No cloud. No telemetry. Your data never leaves your machine.
┌─────────────────────────────────────────────────┐ │ ContextPulse Daemon │ │ │ │ ┌──────────┐ ┌──────────┐ ┌──────────┐ │ │ │ Sight │ │ Voice │ │ Touch │ │ │ │ Screen │ │ Dictate │ │ Keys + │ │ │ │ OCR │ │ Whisper │ │ Mouse │ │ │ │ Clipboard│ │ Vocab │ │ Bursts │ │ │ └────┬─────┘ └────┬─────┘ └────┬─────┘ │ │ └──────────────┼──────────────┘ │ │ ▼ │ │ ┌──────────────┐ │ │ │ EventBus │ │ │ │ (Spine) │ │ │ └──────┬───────┘ │ │ ▼ │ │ ┌──────────────┐ │ │ │ activity.db │ │ │ │ SQLite+FTS5 │ │ │ └──────────────┘ │ └────────────────────┬────────────────────────────┘ │ MCP (streamable-http :8420) ┌────────────┼────────────┐ ▼ ▼ ▼ Claude Code Cursor Any MCP Client
> You: "What am I looking at right now?" Claude calls get_screenshot → get_screen_text: Active window: VS Code, src/auth/middleware.ts OCR text: "export async function validateToken(req: Request)..." Clipboard: "Bearer eyJhbGciOiJIUzI1NiIs..." > Claude: "You're editing the auth middleware in VS Code. > I can see the validateToken function, and you have > a Bearer token in your clipboard. Want me to help > debug the token validation?"
> You hold Ctrl+Space and say: "refactor this to use the new auth provider" ContextPulse Voice transcribes → pastes into editor Claude calls get_recent_transcriptions → get_screen_text: > Claude: "I can see your dictation and the current file. > Here's the refactored middleware using AuthProvider..."
> You: "What was I working on before lunch?" Claude calls get_activity_summary(hours=4) → search_history("auth"): 10:15 AM VS Code, auth/middleware.ts (45 min) 11:00 AM Chrome, JWT.io (12 min) 11:15 AM VS Code, auth/tests/test_middleware.py (30 min) 11:45 AM Slack, #backend channel (15 min) > Claude: "You spent the morning on auth middleware: writing > the implementation, checking JWT specs, then adding > tests. You were in Slack #backend right before lunch."
AI coding assistants are powerful but blind. They can't see your screen, hear your voice notes, or know what you were just doing. ContextPulse bridges this gap:
- Local-first, zero cloud dependency.Your screen, voice, and input data never leave your machine. No accounts, no subscriptions, no third-party servers. Privacy by architecture, not by policy.
- MCP-native from day one.ContextPulse exposes all context as MCP tools. Any MCP client (Claude Desktop, Cursor, Windsurf, VS Code) gets full context without custom integrations.
- True multi-modal in a single daemon.Screen capture, voice dictation, keyboard/mouse input, and semantic memory run in one lightweight process (<1% CPU). No stitching multiple tools together.
- Open source (AGPL-3.0).Fully auditable, self-hostable, and extensible. No vendor lock-in, no SaaS dependency, no risk of acquisition-driven shutdowns.
git clone https://github.com/ContextPulse/contextpulse cd contextpulse # Windows pip install -e packages/core -e packages/screen -e packages/voice -e packages/touch -e packages/project # macOS — the [macos] extras are REQUIRED, not optional niceties. They pull in # pyobjc (clipboard, window, caret, session monitor), rumps (menu bar) and # mlx-whisper (Apple Silicon transcription). Without them the install succeeds # and then fails at runtime. pip install -e "packages/core[macos]" -e "packages/screen[macos]" -e "packages/voice[macos]" \ -e packages/touch -e packages/project # Optional: persistent memory + semantic search pip install -e packages/memory
Configure your AI agent and install companion skills:
contextpulse --setup claude-code # configures MCP + installs skills # or: contextpulse --setup gemini # for Gemini CLI # or: contextpulse --setup all # both
contextpulse # starts the background daemon contextpulse-mcp # starts the MCP server on port 8420
That's it. Your AI agent now has tools for reading your screen, voice, activity, and memory.
{ "mcpServers": { "contextpulse": { "type": "http", "url": "http://127.0.0.1:8420/mcp" } } }
Basic memory isfree forever. No license required.
Memory uses a 3-tier hot/warm/cold architecture: in-memory LRU cache → SQLite WAL + FTS5 → compressed archive. The optionalpip install contextpulse-memorypackage ships these tools.
Pro (4 tools, requires license or 30-day trial)
Free forever:27 tools (Sight × 11, Voice × 3, Touch × 3, Project × 5, Memory × 5)Pro:adds 4 search tools: semantic memory search plus cross-modal event queriesTrial:30-day Pro trial on first use, no credit card required
Additionally, ContextPulse includes several background learning tools (vocabulary consolidation, correction detection) that run automatically to improve transcription quality over time.
ContextPulse is a monorepo with modular packages:
All modules emit events to a sharedEventBus(the "spine"), which writes to a local SQLite database with FTS5 full-text search. MCP servers are read-only processes that query this database.
git clone https://github.com/ContextPulse/contextpulse cd contextpulse uv venv .venv\Scripts\activate uv pip install -e "packages/core[dev]" -e packages/screen -e packages/voice -e packages/touch -e packages/project pytest packages/ -x -q
A canary script exercises every exposed MCP tool and reports pass/fail. It runs automatically on a cron/Task Scheduler schedule to catch regressions before users do.
# Run manually python scripts/canary_health_check.py # Verbose (shows each tool as it runs) python scripts/canary_health_check.py --verbose # JSON output (for CI or external monitoring) python scripts/canary_health_check.py --json
- Auto-starts the ContextPulse daemon if it is not already running
- Calls all primary MCP tools with minimal valid arguments
- Prints a human-readable summary with per-server breakdown
- Appends results tologs/canary_results.json(last 100 runs retained)
- Exits0if all tools pass,1if any fail
- Open Task Scheduler → Create Basic Task
- Trigger: Daily, repeat every 4 hours
- Action: Start a program
- Program:<path-to-contextpulse>\.venv\Scripts\python.exe
- Arguments:scripts/canary_health_check.py
- Start in:<path-to-contextpulse>
ContextPulse is licensed under theGNU Affero General Public License v3.0(AGPL-3.0).
- You can use, modify, and distribute ContextPulse freely
- If you modify and deploy it as a service, you must open-source your changes
- Commercial licensing available for embedding in proprietary products
For commercial licensing inquiries, visitcontextpulse.ai.
ContextPulse's unified multi-modal context delivery system is patent pending.
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