Context Book
@aditya201551
About Context Book
Stop re-explaining yourself to agents. Give it the right context right when it is needed.
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"context-book": {
"url": "https://context-book-mcp-production.up.railway.app"
}
}
}Tools
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Overview
What is Context Book?
Context Book is an MCP server that gives AI tools a persistent, searchable knowledge library, so they don't start from scratch on every conversation. It uses PostgreSQL with pgvector and pg_trgm for storage and Voyage AI for embeddings. The system consists of two Go binaries: an API server for authentication, book/page CRUD, and a dashboard; and an MCP server exposing eight Bearer-authenticated tools for AI agents.
How to use Context Book?
Install prerequisites: Go 1.26+, Node.js 22+, PostgreSQL 16+ with pgvector and pg_trgm extensions, and a Voyage AI API key. Set up the database, configure environment variables, then run go run ./cmd/api/main.go and go run ./cmd/mcp/main.go from the backend directory. Connect any MCP-compatible client by pointing it to http://localhost:8081/mcp, optionally run the frontend with npm run dev in the frontend directory. For Cursor, add the server URL to .cursor/mcp.json.
Key features of Context Book
- Eight MCP tools: create/update/list/get books, insert/update/delete/search pages, and a readme tool.
- Semantic search across all books using Voyage AI embeddings.
- Automatic embedding generation on page insert or update.
- OAuth 2.0 PKCE for the API server; Bearer token authentication for MCP tools.
- Two separate servers: API (REST, port 8080) and MCP (port 8081).
- Optional React frontend dashboard for managing books and pages.
Use cases of Context Book
- Provide AI agents with a persistent knowledge base that survives conversation resets.
- Avoid re-explaining project context, guidelines, or documentation to tools like Claude, Cursor, or Windsurf.
- Organize information into named “books” with ordered “pages” for structured recall.
- Perform semantic searches across all stored content to retrieve relevant context on demand.
FAQ from Context Book
What are the runtime dependencies?
Go 1.26+, Node.js 22+, PostgreSQL 16+ with pgvector and pg_trgm extensions, and a Voyage AI API key.
How do I connect an AI client?
Point the MCP-compatible client to http://localhost:8081/mcp. For Cursor, add the server URL to .cursor/mcp.json as shown in the quick start.
What authentication is used?
The API server uses OAuth 2.0 PKCE. The MCP server requires a Bearer token per request, scoped to the authenticated user.
Where does data live and how is it indexed?
Data is stored in PostgreSQL with pgvector for semantic search and pg_trgm for text matching. Migrations run automatically on API server startup.
What transports and ports are used?
The API server listens on :8080 for REST and the MCP server on :8081 for the MCP protocol over HTTP.
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