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mmmeff

outline-mcp-server

by: mmmeff

outline mcp server

8created 14/03/2025
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📌Overview

Purpose: To provide tools for interacting programmatically with Outline's API, enabling AI agents to manage documents and collections effectively.

Overview: The Model Context Protocol (MCP) server is designed as an interface for the Outline knowledge base platform, allowing users to automate document and collection management through AI integrations.

Key Features:

  • Document Management: Enables users to create, update, retrieve, delete, list, and search documents, ask natural language questions, create document templates, and archive documents.

  • Collection Management: Simplifies the handling of collections by allowing users to list, create, and update collections seamlessly.

  • Comment Management: Facilitates interaction with document comments by permitting users to create, update, and delete comments.

  • User Management: Provides functionalities to list and filter users as needed by the application.

Outline MCP Server

A Model Context Protocol (MCP) server that provides tools for interacting with Outline's API, enabling AI agents to manage documents, collections, and other entities programmatically through the Outline knowledge base platform.

Features

Document Management

  • Create new documents with customizable properties
  • Get document details
  • Update existing documents
  • Delete documents
  • List documents
  • Search documents
  • Ask natural language questions about documents
  • Create templates from existing documents
  • Move documents to different collections or locations
  • Archive documents

Collection Management

  • Get collection details
  • List collections
  • Create and update collections

Comment Management

  • Create comments on documents
  • Update existing comments
  • Delete comments

User Management

  • List and filter users

Note: The SSE server implementation uses Supergateway, which provides more reliable connectivity when used with Cursor's MCP integration.

Quick Start

Prerequisites

  • Node.js (v18 or higher)
  • An Outline account with API access
  • Outline API key with appropriate permissions

Installation

# Run directly with npx
OUTLINE_API_KEY=… npx outline-mcp-server

# or install from npm
npm install -g outline-mcp-server
OUTLINE_API_KEY=… outline-mcp-server

# Run with a custom port (default is 6060)
OUTLINE_API_KEY=… outline-mcp-server --port 7070

Environment Variables

  • OUTLINE_API_KEY (required): your API key for Outline
  • OUTLINE_API_URL (optional): Alternative URL for your Outline API (if using a custom domain or self-hosting)

CLI Options

  • --port <number> (optional): Specify the port on which the server will run (default: 6060)

Usage

Once installed, you can use the MCP server with AI assistants that support the Model Context Protocol, such as Claude via Cursor.

Example queries your AI assistant can now handle:

  • List all the documents in my Outline workspace
  • Create a new document in the 'Product' collection
  • Find all documents related to a specific topic
  • Ask a natural language question about your documents
  • Create a template from an existing document
  • Update the content of a document
  • Add a comment to a document

Development

# Clone this repository
git clone https://github.com/mmmeff/outline-mcp.git
cd outline-mcp

# Install dependencies
npm install

Create a .env file with your Outline API key:

OUTLINE_API_KEY=your_outline_api_key_here
OUTLINE_API_URL=https://your-outline-instance.com/api  # Optional, defaults to https://app.getoutline.com/api

# Build/watch the project alongside running @modelcontextprotocol/inspector
npm run dev

Contributing

This project uses semantic-release for automated versioning and package publishing. Please follow the Conventional Commits specification for your commit messages to ensure proper versioning.

See CONTRIBUTING.md for detailed guidelines on how to contribute to this project.

Release Process

Releases are fully automated using semantic-release and GitHub Actions. When commits are pushed to the master branch, the following happens:

  1. The CI pipeline runs tests and builds the package
  2. semantic-release analyzes commit messages to determine the next version number
  3. A new version is automatically published to npm
  4. A GitHub release is created with auto-generated release notes
  5. The CHANGELOG.md file is updated

No manual version bumping or release creation is needed.

License

MIT