How do I use context-book?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@context-book Search my library for best practices in Go concurrency" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

context-book

by aditya201551

Overview Schema Source Related Servers Discussions Admin

TypeScript

Remote

License: MIT

Stop re-explaining yourself to Agents. Give it the right context, right when needed.

LLMs are stateless — each conversation starts from scratch. ContextBook gives your AI tools a persistent, searchable knowledge library to draw the right context when they need it. No bloatware, no pre-loaded junk. Just the right information, at the right time.

How It Works

flowchart LR
    AI["🤖 AI Clients\nClaude · Cursor · Windsurf"]
    Browser["🌐 Browser Dashboard"]
    MCP["🔌 MCP Server :8081\n8 Bearer-authenticated tools"]
    API["⚙️ REST API :8080\nOAuth 2.0 · Books · Pages · Search"]
    DB["🗄️ PostgreSQL\npgvector · pg_trgm"]
    VOYAGE["🧠 Voyage AI\nvoyage-4 (1024-dim)"]

    AI -- "MCP · Bearer Token" --> MCP
    Browser -- "Session · HTTP JSON" --> API
    MCP --- DB
    API --- DB
    API -- "OAuth 2.0 PKCE" --> AI
    DB --- VOYAGE

Two Go binaries share a PostgreSQL database:

API server (cmd/api) — the control plane: user login, OAuth 2.0, dashboard, book/page CRUD
MCP server (cmd/mcp) — the data plane: 8 MCP tools for AI agents, protected by Bearer tokens

Related MCP server: Librarian

MCP Tools

All tools require a valid Bearer token and are scoped to the authenticated user.

Tool	Description
`book_create_or_update`	Create a Book or update its metadata
`book_list`	Paginated list of Book metadata
`book_get`	Retrieve all pages of a Book
`page_insert`	Push an atomic page into a Book; embeds immediately
`page_update`	Replace a page's content; re-embeds
`page_delete`	Remove a page (indices not re-numbered)
`page_search`	Semantic search across all Books
`readme`	Returns the usage guide (call once per session)

Quick Start

Prerequisites

Go 1.26+
Node.js 22+
PostgreSQL 16+ with pgvector and pg_trgm
A Voyage AI API key

1. Set up the database

CREATE DATABASE contextbook_db;
\c contextbook_db
CREATE EXTENSION IF NOT EXISTS vector;
CREATE EXTENSION IF NOT EXISTS pg_trgm;

Migrations run automatically on API server startup.

2. Configure environment

cp .env.example backend/.env
# Edit backend/.env — set DATABASE_URL, API_KEY_SALT, VOYAGE_API_KEY

3. Run the backend

cd backend
go run ./cmd/api/main.go    # API + dashboard (:8080)
go run ./cmd/mcp/main.go     # MCP server (:8081)

4. Run the frontend (optional)

cd frontend
npm install && npm run dev    # Vite dev server on :5173

5. Connect an AI client

For Cursor (.cursor/mcp.json):

{
  "mcpServers": {
    "contextbook": {
      "url": "http://localhost:8081/mcp"
    }
  }
}

For any MCP-compatible client, point the server URL to http://localhost:8081/mcp.

Documentation

Backend README — API routes, auth flows, database schema, MCP tools, configuration
Frontend README — components, routing, design system, development setup
Architecture — full system overview with Mermaid diagrams

Project Structure

context-book/
├── backend/
│   ├── cmd/api/main.go          REST API + auth server
│   ├── cmd/mcp/main.go          MCP tool server
│   └── internal/
│       ├── api/                  REST handlers + routes
│       ├── auth/                 OAuth 2.0 PKCE, sessions, SSO
│       ├── context/              Book/Page business logic
│       ├── db/                  pgx queries + migrations
│       ├── embedding/            Voyage AI client
│       ├── logger/               slog + HTTP access logging
│       └── mcp/                  8 MCP tool handlers
├── frontend/                     React 19 + Vite + TypeScript SPA
│   └── src/
│       ├── App.tsx               Router + app shell
│       ├── lib/api.ts            HTTP client
│       └── components/           UI components
├── Dockerfile                    API server container
├── Dockerfile.mcp                MCP server container
└── go.work                       Go workspace

Contributing

Fork the repository
Create a feature branch (git checkout -b feature/my-feature)
Make your changes
Ensure the backend compiles (cd backend && go build ./cmd/api ./cmd/mcp)
Ensure the frontend builds (cd frontend && npm run build)
Commit and push
Open a Pull Request

License

MIT — see the LICENSE file for details.

This server cannot be deployed

Context All Your Agents Can ShareAgents share what they learn, hand off work, and hold it when you switch models. Start with 5 GB free.fulcradynamics.comAd

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

Need Help?

Related Servers

Related MCP Connectors

hiveWikiOAuth
ai.hivewiki
Shared project wiki for AI agents: read and write pages, next actions, and activity logs over MCP.
Knowledge & Memory Note Taking Project Management
2
khiveOAuth
ai.khive
Persistent memory, knowledge graph, task management and more for AI agents via MCP.
Knowledge & Memory Project Management
1
Agents Wiki AOAuth
com.agents-wiki
Knowledge base for AI agents: search, read, tasks; write, correct, report outcomes via /mcp/write.
Documentation Access Content Management Systems
1
Levirge BrainOAuth
com.levirge
Shared MCP memory for AI agents: knowledge base, skills, todos and agent-to-agent handoffs.
Knowledge & Memory
1

Related MCP Servers

OpenCode LLM Wiki MCP Server
Knowledge & Memory RAG Systems
Moowningstar
F
license
Not graded
quality
C
maintenance
Enables AI agents to interact with a persistent knowledge graph backend using MCP tools for reading, searching, and analyzing wiki pages with vector search and graph algorithms.
Updated 5 months ago (2026-05-29 15:12 UTC)
4
-
Librarian
Knowledge & Memory Search RAG Systems
arcadeai-labs
A
license
Not graded
quality
B
maintenance
Provides AI agents with persistent knowledge storage, enabling them to store, search, and retrieve text, documents, and files using semantic and keyword search via MCP tools.
Updated 17 days ago (2026-10-01 17:44 UTC)
32
Apache 2.0
AgentBase
vhspace
A
license
Not graded
quality
B
maintenance
Enables AI agents to persistently store and semantically search shared knowledge via MCP tools.
Updated 4 days ago (2026-10-15 15:03 UTC)
2
MIT
engineering-knowledge-mcp
Documentation Access Developer Tools Note Taking
niallr12
F
license
A
quality
C
maintenance
Provides coding agents with a shared, Markdown-based engineering knowledge base to search, capture, create, and update internal conventions, API details, infrastructure configs, and development setup via lightweight MCP tools.
Updated 2 months ago (2026-08-21 22:39 UTC)
6
-