Ganju

Ganju

> Turn your knowledge and integrations into a hosted MCP server that any AI client or chat bot can connect to.

Ganju is an open-source platform for building and hosting Model Context Protocol (MCP) servers. A tenant uploads resources (files, websites, cloud drives), wires up tools (Gmail, Slack, Calendar, web search, or their own HTTP/MCP backends), writes prompts, and gets a ready-to-use MCP endpoint at https://mcp./ — reachable from Claude Desktop, ChatGPT, Cursor, and from chat bots on Telegram, Slack, WhatsApp, and Discord.

It runs almost entirely on the Cloudflare developer platform (Workers, Queues, R2, Hyperdrive, Containers, Durable Objects) with Postgres + pgvector for storage and retrieval.

Features

• Hosted MCP servers — each "artifact" becomes a stateless MCP server with its own slug, OAuth, and tool set.
• RAG over your content — upload files, crawl websites, or sync Google Drive / OneDrive folders; content is chunked and embedded for vector search.
• A growing tool catalog — native integrations (Gmail, Outlook, Slack, Google Calendar, Cal.com, Tavily web search) plus two generic, no-code definitions:
• http-endpoint — expose your own HTTP API as a tool.
• mcp-proxy — connect a vendor's official MCP server (Notion, GitHub, …) and re-expose its tools.
• Chat-channel bots — the same artifact can drive Telegram / Slack / WhatsApp / Discord bots through an LLM tool-calling loop (Gemini, Claude, or OpenAI).
• Multi-tenant — organizations → projects → artifacts, with invitations and roles.
• Audit & usage trails — every MCP request, tool call, and channel message is recorded.

Architecture at a glance

flowchart LR
  subgraph Clients
    A[MCP clientsClaude / ChatGPT / Cursor]
    B[Chat botsTelegram / Slack / WhatsApp / Discord]
    C[Dashboard users]
  end

  A -->|MCP over HTTP| MCP[apps/mcpMCP server Worker]
  B -->|webhooks| API[apps/apicontrol-plane Worker]
  C --> WEB[apps/webNext.js dashboard]
  WEB -->|REST| API

  API --> DB[(Postgres + pgvectorvia Hyperdrive)]
  MCP --> DB
  API --> Q[[Cloudflare Queues]]
  Q --> API
  API --> RH[apps/resource-handlerNode container]
  MCP --> RH
  API --> R2[(R2 storage)]

| App | Runtime | Responsibility | | ------------------------------------------------ | ------------------------------- | ----------------------------------------------------------------------------------------- | | [apps/api](apps/api) | Cloudflare Worker (Hono) | Control plane: auth, CRUD, OAuth, channel webhooks, queue consumers | | [apps/mcp](apps/mcp) | Cloudflare Worker (Hono) | The MCP server itself — boots a server per request and dispatches tools/resources/prompts | | [apps/resource-handler](apps/resource-handler) | Node container | CPU/binary-heavy work: document extraction, web crawling, large file sends | | [apps/web](apps/web) | Next.js (OpenNext → Cloudflare) | The management dashboard |

See [docs/ARCHITECTURE.md](docs/ARCHITECTURE.md) for the full picture.

Repository layout

ganju/
├── apps/
│   ├── api/              Control-plane Worker (Hono)
│   ├── mcp/              MCP-server Worker (Hono)
│   ├── resource-handler/ Node container for heavy work
│   └── web/              Next.js dashboard
├── packages/
│   ├── db/               Drizzle schema, migrations, connection
│   ├── utils/            Shared kernel: constants, crypto, oauth, chunking, send helpers
│   ├── ui/               MUI component library
│   ├── containers/       Cloudflare Container class wrapper
│   └── tsconfig/         Shared TypeScript config
├── docs/                 Project documentation (start here)
└── scripts/              Dev tooling

It's an npm workspaces + Turborepo monorepo.

Quick start

npm install
cp .env.example .env      # then fill in the values
npm run migrate-dev       # generate + apply DB migrations
npm run dev               # start all apps via turbo

Default local ports: API 8080, MCP 8081, resource-handler 8082, web 3000.

Full setup (prerequisites, environment variables, database, per-app commands) is in [docs/DEVELOPMENT.md](docs/DEVELOPMENT.md).

Tech stack

• Language: TypeScript everywhere
• Edge runtime: Cloudflare Workers, Queues, R2, Hyperdrive, Durable Objects, Containers
• Web framework: Hono (APIs) and Next.js (dashboard)
• Database: Postgres + pgvector, accessed with Drizzle ORM
• Auth: better-auth (social login + OIDC provider for MCP OAuth)
• AI: Gemini, Anthropic, and OpenAI SDKs; Gemini embeddings for RAG
• MCP: @modelcontextprotocol/sdk

Documentation

| Doc | What's inside | | ------------------------------------------------------------ | --------------------------------------------------- | | [docs/ARCHITECTURE.md](docs/ARCHITECTURE.md) | System design, apps, data flow, Cloudflare bindings | | [docs/DEVELOPMENT.md](docs/DEVELOPMENT.md) | Local setup, env vars, commands, troubleshooting | | [docs/DATAMODEL.md](docs/DATAMODEL.md) | Database entities and relationships | | [docs/DEPLOYMENT.md](docs/DEPLOYMENT.md) | Deploying to Cloudflare, environments, secrets | | [apps/mcp/src/tools/README.md](apps/mcp/src/tools/README.md) | How tools work and how to add one | | [CONTRIBUTING.md](CONTRIBUTING.md) | Contribution workflow and conventions |

Contributing

Contributions are welcome — please read [CONTRIBUTING.md](CONTRIBUTING.md) first.

License

[Apache-2.0](LICENSE) — see also [NOTICE](NOTICE).

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: MontoyaAndres
• Source: MontoyaAndres/ganju
• License: Apache-2.0
• Homepage: https://ganju.ai

Install and usage instructions live in the source repository linked above.