mcp-outline 1.2.0

A Model Context Protocol (MCP) server for Outline (https://www.getoutline.com)

MCP Outline Server

A Model Context Protocol server for interacting with Outline document management.

Features

• Document operations: Search, read, create, edit, archive documents
• Collections: List, create, manage document hierarchies
• Comments: Add and view threaded comments
• Backlinks: Find documents referencing a specific document
• MCP Resources: Direct content access via URIs (outline://document/{id}, outline://collection/{id}, etc.)
• Automatic rate limiting: Transparent handling of API limits with retry logic

Installation

Using uv (Recommended)

uvx mcp-outline

Using pip

pip install mcp-outline

Using Docker

docker run -e OUTLINE_API_KEY=<your-key> ghcr.io/vortiago/mcp-outline:latest

Or build from source:

docker buildx build -t mcp-outline .
docker run -e OUTLINE_API_KEY=<your-key> mcp-outline

Configuration

Variable	Required	Default	Notes
OUTLINE_API_KEY	Yes	-	API token from Outline Settings → API Keys
OUTLINE_API_URL	No	https://app.getoutline.com/api	Self-hosted Outline: https://your-domain/api
OUTLINE_DISABLE_AI_TOOLS	No	-	Set to true to disable AI tools (for instances without OpenAI)
MCP_TRANSPORT	No	stdio	stdio, sse, or streamable-http
MCP_HOST	No	127.0.0.1	Use 0.0.0.0 in Docker for external access
MCP_PORT	No	3000	HTTP server port (for sse/streamable-http)

Adding to Your Client

Prerequisites: Install uv with pip install uv or from astral.sh/uv

Add to Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (or %APPDATA%\Claude\claude_desktop_config.json on Windows):

{
  "mcpServers": {
    "mcp-outline": {
      "command": "uvx",
      "args": ["mcp-outline"],
      "env": {
        "OUTLINE_API_KEY": "<YOUR_API_KEY>",
        "OUTLINE_API_URL": "<YOUR_OUTLINE_URL>" // Optional
      }
    }
  }
}

Add to Cursor

Go to Settings → MCP and click Add Server:

{
  "mcp-outline": {
    "command": "uvx",
    "args": ["mcp-outline"],
    "env": {
      "OUTLINE_API_KEY": "<YOUR_API_KEY>",
      "OUTLINE_API_URL": "<YOUR_OUTLINE_URL>" // Optional
    }
  }
}

Add to VS Code

Create a .vscode/mcp.json file in your workspace with the following configuration:

{
  "servers": {
    "mcp-outline": {
      "type": "stdio",
      "command": "uvx",
      "args": ["mcp-outline"],
      "env": {
        "OUTLINE_API_KEY": "<YOUR_API_KEY>"
      }
    }
  }
}

For self-hosted Outline instances, add OUTLINE_API_URL to the env object.

Optional: Use input variables for sensitive credentials:

{
  "inputs": [
    {
      "type": "promptString",
      "id": "outline-api-key",
      "description": "Outline API Key",
      "password": true
    }
  ],
  "servers": {
    "mcp-outline": {
      "type": "stdio",
      "command": "uvx",
      "args": ["mcp-outline"],
      "env": {
        "OUTLINE_API_KEY": "${input:outline-api-key}"
      }
    }
  }
}

VS Code will automatically discover and load MCP servers from this configuration file. For more details, see the official VS Code MCP documentation.

Add to Cline (VS Code)

In Cline extension settings, add to MCP servers:

{
  "mcp-outline": {
    "command": "uvx",
    "args": ["mcp-outline"],
    "env": {
      "OUTLINE_API_KEY": "<YOUR_API_KEY>",
      "OUTLINE_API_URL": "<YOUR_OUTLINE_URL>" // Optional
    }
  }
}

Using pip instead of uvx

If you prefer to use pip instead:

pip install mcp-outline

Then in your client config, replace "command": "uvx" with "command": "mcp-outline" and remove the "args" line:

{
  "mcp-outline": {
    "command": "mcp-outline",
    "env": {
      "OUTLINE_API_KEY": "<YOUR_API_KEY>",
      "OUTLINE_API_URL": "<YOUR_OUTLINE_URL>" // Optional
    }
  }
}

Docker Deployment (HTTP)

For remote access or Docker containers, use HTTP transport. This runs the MCP server on port 3000:

docker run -p 3000:3000 \
  -e OUTLINE_API_KEY=<YOUR_API_KEY> \
  -e MCP_TRANSPORT=streamable-http \
  ghcr.io/vortiago/mcp-outline:latest

Then connect from client:

{
  "mcp-outline": {
    "url": "http://localhost:3000/mcp"
  }
}

Note: OUTLINE_API_URL should point to where your Outline instance is running, not localhost:3000.

Tools

Search & Discovery

• search_documents(query, collection_id?, limit?, offset?) - Search documents by keywords with pagination
• list_collections() - List all collections
• get_collection_structure(collection_id) - Get document hierarchy within a collection
• get_document_id_from_title(query, collection_id?) - Find document ID by title search

Document Reading

• read_document(document_id) - Get document content
• export_document(document_id) - Export document as markdown

Document Management

• create_document(title, collection_id, text?, parent_document_id?, publish?) - Create new document
• update_document(document_id, title?, text?, append?) - Update document (append mode available)
• move_document(document_id, collection_id?, parent_document_id?) - Move document to different collection or parent

Document Lifecycle

• archive_document(document_id) - Archive document
• unarchive_document(document_id) - Restore document from archive
• delete_document(document_id, permanent?) - Delete document (or move to trash)
• restore_document(document_id) - Restore document from trash
• list_archived_documents() - List all archived documents
• list_trash() - List all documents in trash

Comments & Collaboration

• add_comment(document_id, text, parent_comment_id?) - Add comment to document (supports threaded replies)
• list_document_comments(document_id, include_anchor_text?, limit?, offset?) - View document comments with pagination
• get_comment(comment_id, include_anchor_text?) - Get specific comment details
• get_document_backlinks(document_id) - Find documents that link to this document

Collection Management

• create_collection(name, description?, color?) - Create new collection
• update_collection(collection_id, name?, description?, color?) - Update collection properties
• delete_collection(collection_id) - Delete collection
• export_collection(collection_id, format?) - Export collection (default: outline-markdown)
• export_all_collections(format?) - Export all collections

Batch Operations

• batch_create_documents(documents) - Create multiple documents at once
• batch_update_documents(updates) - Update multiple documents at once
• batch_move_documents(document_ids, collection_id?, parent_document_id?) - Move multiple documents
• batch_archive_documents(document_ids) - Archive multiple documents
• batch_delete_documents(document_ids, permanent?) - Delete multiple documents

AI-Powered

• ask_ai_about_documents(question, collection_id?, document_id?) - Ask natural language questions about your documents

Resources

• outline://collection/{id} - Collection metadata (name, description, color, document count)
• outline://collection/{id}/tree - Hierarchical document tree structure
• outline://collection/{id}/documents - Flat list of documents in collection
• outline://document/{id} - Full document content (markdown)
• outline://document/{id}/backlinks - Documents that link to this document

Development

Quick Start with Self-Hosted Outline

# Generate configuration
cp config/outline.env.example config/outline.env
openssl rand -hex 32 > /tmp/secret_key && openssl rand -hex 32 > /tmp/utils_secret
# Update config/outline.env with generated secrets

# Start all services
docker compose up -d

# Create API key: http://localhost:3030 → Settings → API Keys
# Add to .env: OUTLINE_API_KEY=<token>

Setup

git clone https://github.com/Vortiago/mcp-outline.git
cd mcp-outline
uv pip install -e ".[dev]"

Testing

# Run tests
uv run pytest tests/

# Format code
uv run ruff format .

# Type check
uv run pyright src/

# Lint
uv run ruff check .

Running Locally

uv run mcp-outline

Testing with MCP Inspector

Use the MCP Inspector to test the server tools visually via an interactive UI.

For local development (with stdio):

npx @modelcontextprotocol/inspector -e OUTLINE_API_KEY=<your-key> -e OUTLINE_API_URL=<your-url> uv run python -m mcp_outline

For Docker Compose (with HTTP):

npx @modelcontextprotocol/inspector http://localhost:3000

Architecture Notes

Rate Limiting: Automatically handled via header tracking (RateLimit-Remaining, RateLimit-Reset) with exponential backoff retry (up to 3 attempts). No configuration needed.

Transport Modes:

• stdio (default): Direct process communication
• sse: HTTP Server-Sent Events (use for web clients)
• streamable-http: Streamable HTTP transport

Connection Pooling: Shared httpx connection pool across instances (configurable: OUTLINE_MAX_CONNECTIONS=100, OUTLINE_MAX_KEEPALIVE=20)

Contributing

Contributions welcome! Please submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Built with MCP Python SDK
• Uses Outline API for document management