Impri

by sekera-radim

296 downloads

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GitHub Website

About

Human-in-the-loop approval inbox for AI agents. An agent proposes an action, a human approves or rejects it, then it runs. Watchers + approval inbox, MCP + REST, self-hostable (MIT).

Details

Author: sekera-radim
Downloads: 296
Categories: AI

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 Impri

Command (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

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

From the repository

The README includes setup instructions such as docker compose up.

`impri_push_action`

Submit an action to the Impri human-approval inbox. The action appears in the operator's web and mobile inbox as a card with a title, formatted preview, and optional tap-to-edit fields. The operator approves or rejects with one tap; you poll for the decision with impri_await_decision. Returns { action_id, status: "pending", inbox_url }. Save action_id — you need it for all follow-up calls. Example — send a draft Reddit reply for review: kind: "reddit.comment" title: "Reply: Why is resume advice so conflicting?" preview: { format: "markdown", body: "The advice conflicts because different advisors optimise for different audiences..." } target_url: "https://reddit.com/r/cscareerquestions/comments/..." editable: ["preview.body"] // lets the reviewer tweak wording before approving

`impri_await_decision`

Poll until the human approves, rejects, or the timeout elapses. Checks GET /actions/:id every 5 seconds and returns as soon as the action leaves the pending state. Decision meanings: "approved" — proceed with the action; any reviewer edits are included in preview/payload "rejected" — abort; respect the decision and do not proceed "expired" — the approval window closed; create a new action if the task is still relevant On timeout the action stays pending in the inbox. Call impri_inbox_status to check queue depth and consider pausing further submissions. Typical usage: 1. impri_push_action → get action_id 2. impri_await_decision(action_id) → wait for human decision 3. If approved: execute the action, then impri_report_result(action_id, "executed")

`impri_report_result`

Report whether you successfully executed an approved action. Closes the audit loop — the operator sees 'executed' or 'execute_failed' in the inbox alongside the original action and decision. Always call this after attempting an approved action, even on failure. Statuses: "executed" — action was carried out successfully "execute_failed" — execution attempt failed (include the error in detail)

`impri_inbox_status`

Check how many actions are waiting for human decisions. Returns the pending count and a brief list of pending action titles. Call this before starting a large batch of tasks — if the inbox is backed up, pause and let the operator catch up to avoid actions expiring before they are reviewed.

`impri_create_watcher`

Create a watcher that monitors external sources (RSS feeds, Reddit, URL diffs) and delivers matching items to the approval inbox or a webhook. The watcher runs on the schedule you specify, deduplicates items by URL/content-hash, and delivers only new matches. The first run establishes a baseline and does not generate alerts. Example — watch an RSS feed for AI-related news: spec: { name: "AI launches radar", kind: "rss", config: { url: "https://openai.com/news/rss.xml" }, keywords: ["launch", "gpt-", "voice"], keywords_none: ["funding", "benchmark"], min_score: 1, schedule: { every: "8h", jitter: "4h" } } Returns { watcher_id, name, kind, status, next_run_at }.

`impri_list_watchers`

List all configured watchers, optionally filtered by status. Returns the watcher count and a summary line per watcher (id, name, kind, status). Use this to audit what is being monitored, check for degraded watchers, or find a watcher_id for further operations.

`impri_list_watcher_presets`

List all available watcher presets with their parameters. Presets are pre-configured watcher templates for common sources (Hacker News, Reddit, GitHub, npm, YouTube, arXiv, etc.). Each preset has an id, a human-readable title, required and optional params, and a default schedule. Call this first to discover which preset fits your monitoring goal, then use impri_create_watcher_from_preset to create the watcher by supplying only the preset_id and param values. No deep knowledge of watcher config schemas is needed. Example output: Community: - hn-front-page: "Hacker News Front Page" (rss) — no params required - reddit-keyword: "Reddit – Keyword Search" (reddit_search) — params: query, [subreddit]

`impri_create_watcher_from_preset`

Create a watcher from a preset template by supplying the preset id and param values. Presets handle all watcher config construction — URL building, keyword setup, SSRF validation — so you only provide the param values listed by impri_list_watcher_presets. The schedule defaults to the preset's recommended interval but can be overridden. The name defaults to "{preset title}: {primary param value}" if omitted. Returns { watcher_id, name, kind, status, next_run_at }. Examples: Watch the HN front page (no params needed): preset_id: "hn-front-page" params: {} Watch a subreddit for new posts: preset_id: "reddit-subreddit" params: { subreddit: "MachineLearning" } Watch a GitHub repo for new releases, check every 2 hours: preset_id: "github-releases" params: { owner: "fastify", repo: "fastify" } schedule: { every: "2h" } Watch HN for keyword with a custom min_points threshold: preset_id: "hn-keyword" params: { keyword: "rust programming", min_points: "25" }

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "impri": {
            "impri": {
                "command": "npx",
                "args": [
                    "@impri/mcp"
                ],
                "env": {
                    "IMPRI_API_KEY": "im_your_key_here"
                }
            }
        }
    }
}

McpServers

{
    "impri": {
        "command": "npx",
        "args": [
            "@impri/mcp"
        ],
        "env": {
            "IMPRI_API_KEY": "im_your_key_here"
        }
    }
}

Impri — Approval Inbox for AI Agents

> The imprimatur for your AI agents. Watchers watch the world, the Approval
> Inbox holds the agent's hands until a human says yes.

Quickstart

Docker Compose (< 5 minutes)

git clone https://gitlab.com/sekera.radim/impri.git
cd impri
docker compose up

Open http://localhost:8080 in your browser.

On first start the server prints the bootstrap Admin API key to the logs:

╔══════════════════════════════════════════════════════╗
║            IMPRI — FIRST RUN BOOTSTRAP               ║
╠══════════════════════════════════════════════════════╣
║  Admin API Key: im_...                               ║
║  Project ID:    proj_...                             ║
║  Store this key securely — it will not be shown again.║
╚══════════════════════════════════════════════════════╝

Copy the key, paste it into the login screen, and you're in.

Dev mode (hot-reload)

Terminal 1 — server:

```bash
cd server
npm install
npm run dev

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About

Details

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Setting up with Highlight

From the repository

impri_push_action

impri_await_decision

impri_report_result

impri_inbox_status

impri_create_watcher

impri_list_watchers

impri_list_watcher_presets

impri_create_watcher_from_preset

Claude Desktop / Cursor

McpServers

Impri — Approval Inbox for AI Agents

Quickstart

Docker Compose (< 5 minutes)

Dev mode (hot-reload)

Install

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`impri_push_action`

`impri_await_decision`

`impri_report_result`

`impri_inbox_status`

`impri_create_watcher`

`impri_list_watchers`

`impri_list_watcher_presets`

`impri_create_watcher_from_preset`