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docs: mcp support
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Timothy Jaeryang Baek
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title: "❓ FAQ"
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docs/openapi-servers/mcp.mdx
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title: "🛰️ MCP Support"
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This documentation explains how to easily set up and deploy the **MCP (Model Context Protocol)-to-OpenAPI proxy server** provided by Open WebUI. Learn how you can effortlessly expose MCP-based tool servers using standard, familiar OpenAPI endpoints suitable for end-users and developers.
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### 📌 What is the MCP Proxy Server?
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The MCP-to-OpenAPI proxy server lets you use tool servers implemented with MCP (Model Context Protocol) directly via standard REST/OpenAPI APIs—no need to manage unfamiliar or complicated custom protocols. If you're an end-user or application developer, this means you can interact easily with powerful MCP-based tooling directly through familiar REST-like endpoints.
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### ✅ Quickstart: Running the Proxy Locally
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Here's how simple it is to launch the MCP-to-OpenAPI proxy server and expose tools already available from an MCP server:
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1. **Prerequisites**
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- **Python 3.8+** with `pip` installed.
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- (Optional) `uv` installed to run the MCP server.
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2. **Clone the Repository & Install Dependencies**
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```bash
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git clone https://github.com/open-webui/openapi-servers
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cd openapi-servers/servers/mcp-proxy
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pip install -r requirements.txt
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```
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3. **Run The Proxy Server**
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Simply type:
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```bash
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python main.py --host 0.0.0.0 --port 8000 -- uvx mcp-server-time --local-timezone=America/New_York
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```
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- Replace `uvx mcp-server-time [options]` above with your custom MCP server command.
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### 🚀 Accessing the Generated APIs
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As soon as it starts, the MCP Proxy automatically:
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- Discovers available MCP tools dynamically and generates REST endpoints.
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- Creates human-readable documentation accessible from the built-in interactive API page at: http://localhost:8000/docs
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- Now, simply call the generated API endpoints directly or use them with your AI agents or API clients!
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### 📖 Example Workflow for End-Users
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Assuming you ran the MCP command above (`uvx mcp-server-time`):
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- Visit your local URL (`http://localhost:8000/docs`)
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- Find the generated endpoint (e.g. `/get_current_time`) and use the easy interactive form provided by FastAPI.
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- Click "**Execute**", and immediately see the response output.
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You now have standard OpenAPI REST APIs made available instantly without complex setups.
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## 🚀 Deploying in Production (Example)
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Deploying your MCP-to-OpenAPI proxy to a production environment is easy. Here's a concise step-by-step example using Docker and popular deployment environments like cloud hosting or VPS.
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### 🐳 Dockerize your Proxy Server
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1. **Create a Dockerfile** (`Dockerfile`) inside your proxy server directory (`servers/mcp-proxy`):
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```dockerfile
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FROM python:3.11-slim
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WORKDIR /app
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COPY . /app
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RUN pip install -r requirements.txt
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# Replace with your MCP server command; example: uvx mcp-server-time
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CMD ["python", "main.py", "--host", "0.0.0.0", "--port", "8000", "--", "uvx", "mcp-server-time", "--local-timezone=America/New_York"]
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```
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2. **Build & Run the Container Locally**
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```bash
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docker build -t mcp-proxy-server .
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docker run -d -p 8000:8000 mcp-proxy-server
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```
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3. **Deploy to Production (AWS/Cloud/VPS Example)**
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- Push the Docker image to DockerHub or your favorite registry:
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```bash
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docker tag mcp-proxy-server yourdockerusername/mcp-proxy-server:latest
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docker push yourdockerusername/mcp-proxy-server:latest
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```
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- Use Docker Compose, Kubernetes manifests, or deploy directly to AWS ECS, Azure Container Instances, Render.com Containers, Heroku, or your desired cloud hosting platform.
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✔️ **Production-ready** — your MCP servers are now exposed and safely accessible using industry-standard REST APIs!
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## 🧑💻 Technical Details and Background
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### 🍃 How It Works (Technical Summary)
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- **Dynamic Schema Discovery & Endpoints:** At server startup, the proxy connects to the MCP server to query available tools. It automatically builds FastAPI endpoints based on the MCP tool schemas, creating concise and clear REST endpoints.
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- **OpenAPI Auto-documentation:** Endpoints generated are seamlessly documented and available via FastAPI's built-in Swagger UI (`/docs`). No extra doc writing required.
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- **Asynchronous & Performant**: Built on robust asynchronous libraries, ensuring speed and reliability for concurrent users.
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### 📚 Under the Hood:
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- FastAPI (Automatic routing & docs generation)
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- MCP Client (Standard MCP integration & schema discovery)
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- Standard JSON over HTTP (Easy integration)
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## ⚡️ Why is the MCP-to-OpenAPI Proxy Superior?
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Here's why leveraging MCP servers through OpenAPI via the proxy approach is significantly better and why Open WebUI enthusiastically supports it:
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- **User-friendly & Familiar Interface**: No custom clients; just HTTP REST endpoints you already know.
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- **Instant Integration**: Immediately compatible with thousands of existing REST/OpenAPI tools, SDKs, and services.
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- **Powerful & Automatic Docs**: Built-in Swagger UI documentation is automatically generated, always accurate, and maintained.
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- **No New Protocol overhead**: Eliminates the necessity to directly handle MCP-specific protocol complexities and socket communication issues.
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- **Battle-Tested Security & Stability**: Inherits well-established HTTPS transport, standard auth methods (JWT, API keys), solid async libraries, and FastAPI’s proven robustness.
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- **Future-Proof**: MCP proxy uses existing, stable, standard REST/OpenAPI formats guaranteed long-term community support and evolution.
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🌟 **Bottom line:** MCP-to-OpenAPI makes your powerful MCP-based AI tools broadly accessible through intuitive, reliable, and scalable REST endpoints. Open WebUI proudly supports and recommends this best-in-class approach.
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## 📢 Community & Support
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- For questions, suggestions, or feature requests, please use our [GitHub Issue tracker](https://github.com/open-webui/openapi-servers/issues) or join our [Community Discussions](https://github.com/open-webui/openapi-servers/discussions).
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Happy integrations! 🌟🚀
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