Outline MCP Server Integration

What does “Outline” MCP Server do?

The Outline MCP Server is a Model Context Protocol (MCP) server that enables AI assistants to seamlessly interact with Outline documentation services. By acting as a bridge between natural language commands and Outline’s robust document management APIs, it empowers AI agents to perform tasks such as searching documents, managing document collections, reading or editing content, and handling comments—all through a secure, programmable interface. This integration enhances developer workflows by automating knowledge management, streamlining documentation processes, and enabling richer, context-aware AI interactions with organizational knowledge bases.

List of Prompts

No explicit prompt templates are described in the repository or documentation.

List of Resources

No explicit MCP resources are detailed in the repository or documentation.

List of Tools

• Document Search: Search for documents within Outline by keywords.
• Collection Management: List available collections and view their document structures.
• Document Reading: Retrieve document content and export it as markdown.
• Comment Management: View and add comments on documents.
• Document Creation: Create new documents within specified collections.
• Document Editing: Update document content and move documents between collections.
• Backlink Management: View documents that link to a specific document.

Use Cases of this MCP Server

• Knowledge Base Search: Developers and AI assistants can quickly search organizational documentation for relevant information or answers using natural language queries.
• Automated Documentation Updates: AI agents can create, update, or move documents programmatically, ensuring documentation stays up-to-date with minimal manual intervention.
• Content Summarization and Reading: Retrieve and process document content for summarization or review, streamlining knowledge absorption and sharing.
• Collaboration and Feedback: Add and manage comments on documents, enhancing team collaboration and review workflows directly from AI-powered assistants.
• Organizational Insights: Analyze backlinks to understand document relationships and knowledge flows across the organization.

How to set it up

Windsurf

No Windsurf-specific setup instructions are provided.

Claude

No Claude-specific setup instructions are provided.

Cursor

1. Install Docker: Ensure Docker or Docker Desktop is installed and running.
2. Build the Docker Image:

   docker buildx build -t mcp-outline .
   

3. Add the MCP Server in Cursor:
   • Go to the “MCP Servers” tab and click “Add Server”.
   • Use the following JSON configuration:

     {
       "mcpServers": {
         "mcp-outline": {
           "command": "docker",
           "args": [
             "run",
             "-i",
             "--rm",
             "--init",
             "-e",
             "DOCKER_CONTAINER=true",
             "-e",
             "OUTLINE_API_KEY",
             "-e",
             "OUTLINE_API_URL",
             "mcp-outline"
           ],
           "env": {
             "OUTLINE_API_KEY": "<YOUR_OUTLINE_API_KEY>",
             "OUTLINE_API_URL": "<YOUR_OUTLINE_API_URL>"
           }
         }
       }
     }
     

4. Set Environment Variables:
   Use your Outline API key (mandatory) and API URL (optional, defaults to https://app.getoutline.com/api).
5. Debug and Inspect (optional):

   npx @modelcontextprotocol/inspector docker run -i --rm --init -e DOCKER_CONTAINER=true --env-file .env mcp-outline
   

Securing API Keys

Store your keys in environment variables. Example:

"env": {
  "OUTLINE_API_KEY": "<YOUR_OUTLINE_API_KEY>",
  "OUTLINE_API_URL": "<YOUR_OUTLINE_API_URL>"
}

Cline

No Cline-specific setup instructions are provided.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "mcp-outline": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “mcp-outline” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Our opinion

The Outline MCP Server provides robust document management tooling for AI integrations, with clear Docker-based setup instructions and practical tools for Outline users. However, the lack of explicit prompt templates and documented resources limits its out-of-the-box versatility. Its score is above average for developer usability due to setup clarity and tool coverage, but could be improved with more resource and prompt formalization.

MCP Score