# Ganju > Ganju.ai is a no-code tool for creating fast and scalable MCP servers. - **Type:** MCP server - **Install:** `agentstack add mcp-montoyaandres-ganju` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [MontoyaAndres](https://agentstack.voostack.com/s/montoyaandres) - **Installs:** 0 - **Category:** [Integrations](https://agentstack.voostack.com/c/integrations) - **Latest version:** 0.1.0 - **License:** Apache-2.0 - **Upstream author:** [MontoyaAndres](https://github.com/MontoyaAndres) - **Source:** https://github.com/MontoyaAndres/ganju - **Website:** https://ganju.ai ## Install ```sh agentstack add mcp-montoyaandres-ganju ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # 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](https://modelcontextprotocol.io) (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 ```mermaid 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](https://docs.npmjs.com/cli/using-npm/workspaces) + [Turborepo](https://turbo.build/) monorepo. ## Quick start ```bash 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](https://hono.dev) (APIs) and [Next.js](https://nextjs.org) (dashboard) - **Database:** Postgres + [`pgvector`](https://github.com/pgvector/pgvector), accessed with [Drizzle ORM](https://orm.drizzle.team) - **Auth:** [better-auth](https://www.better-auth.com) (social login + OIDC provider for MCP OAuth) - **AI:** Gemini, Anthropic, and OpenAI SDKs; Gemini embeddings for RAG - **MCP:** [`@modelcontextprotocol/sdk`](https://github.com/modelcontextprotocol/typescript-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/DATA_MODEL.md](docs/DATA_MODEL.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](https://github.com/MontoyaAndres) - **Source:** [MontoyaAndres/ganju](https://github.com/MontoyaAndres/ganju) - **License:** Apache-2.0 - **Homepage:** https://ganju.ai Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** yes - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/mcp-montoyaandres-ganju - Seller: https://agentstack.voostack.com/s/montoyaandres - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.