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MCP Server

Raven Docs includes a Model Context Protocol (MCP) server that allows AI agents to interact with your knowledge base.

What is MCP?​

The Model Context Protocol is a standard for connecting AI assistants to external tools and data sources. It enables AI agents to:

  • Read and search your documentation
  • Create and update content
  • Manage tasks and projects
  • Store persistent memory

Architecture​

Key Features​

100+ Tools​

Access all Raven Docs functionality through standardized tools:

CategoryTools
SpacesCreate, list, update, delete spaces
PagesFull CRUD, history, search
TasksManage tasks and projects
UsersList and manage users
SearchFull-text search
MemoryStore and query agent memory

Tool Discovery​

Agents can search for relevant tools without loading the entire catalog:

{
  "name": "tool_search",
  "arguments": {
    "query": "create page",
    "limit": 5
  }
}

Agent Memory​

Store persistent context between conversations:

{
  "name": "memory_ingest",
  "arguments": {
    "workspaceId": "ws_123",
    "content": "User prefers formal documentation style",
    "tags": ["preferences", "style"]
  }
}

Use Cases​

AI Documentation Assistant​

Build an AI assistant that can answer questions using your documentation:

const response = await agent.run({
  messages: [
    { role: 'user', content: 'How do I set up authentication?' }
  ],
  tools: mcpTools,
});
// Agent searches docs and provides answer with sources

Automated Documentation Updates​

Keep documentation in sync with code changes:

// When API changes are detected
await mcpClient.callTool('page_update', {
  pageId: 'api-reference',
  content: generateApiDocs(newSchema),
});

Intelligent Chatbot​

Create a chatbot with full knowledge of your product:

// Chatbot uses MCP to search knowledge base
const results = await mcpClient.callTool('search_query', {
  workspaceId: 'ws_123',
  query: userQuestion,
});

Research Agents​

Build agents that can research topics across your docs:

await mcpClient.callTool('research_create', {
  workspaceId: 'ws_123',
  spaceId: 'space_456',
  topic: 'competitor analysis',
});

Quick Start​

  1. Get an API key from Settings → API Keys
  2. Configure your MCP client
  3. Start using tools
{
  "mcpServers": {
    "raven-docs": {
      "url": "http://localhost:3000/api/mcp-standard",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}

See the Quickstart Guide for detailed setup.

Endpoints​

EndpointDescription
POST /mcp-standard/initializeInitialize connection
POST /mcp-standard/list_toolsList all tools
POST /mcp-standard/search_toolsSearch for tools
POST /mcp-standard/call_toolExecute a tool
POST /mcp-standard/list_categoriesList tool categories