mcpField
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Auto MCP

Auto MCP

Local
automcp.brizz.aiDeveloper Tools194Updated 73w ago

About Auto MCP

Auto MCP turns OpenAPI or Swagger definitions into MCP servers that proxy requests to a configured upstream endpoint. It runs locally, in Claude Desktop, or in the cloud, and suits developers who want to expose existing REST APIs quickly.

Key features

  1. 01Generates routes from Swagger 2.0 and OpenAPI v3 documents
  2. 02Supports stdio, http and sse transport modes
  3. 03Offers bearer, basic, API key and OAuth 2.1 authentication
  4. 04Configurable via YAML, CLI flags or AUTO_MCP_ environment variables
  5. 05TUI tool for filtering routes and editing endpoint descriptions

Use cases

  1. 01Wrapping an existing REST API as an MCP server for prototyping
  2. 02Exposing legacy or internal systems to AI assistants without rewriting them
  3. 03Running a Dockerized MCP server inside Claude Desktop

MCP support

Auto MCP is an MCP server that exposes each endpoint from an OpenAPI document as an MCP tool, served over stdio, http or sse to MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"auto-mcp-brizzai": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"\\"
]
}
}
}
Run commanddocker run -i --rm '\'

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
oci\

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Auto MCP

Visit the Auto MCP Homepage

Go Report Card GitHub release (latest by date) License Go version Container Registry Build Status

Transform any OpenAPI/Swagger definition into a fully-featured Model Context Protocol (MCP) server – ready to run locally, inside Claude Desktop, or in the cloud.

The service reads a Swagger (OpenAPI v2) or OpenAPI v3 document, generates routes on-the-fly, proxies requests to the upstream endpoint you configure, and exposes them through MCP using either the STDIO or HTTP or SSE transport defined in the MCP specification.


✨ Why Auto MCP?

  • Zero boiler-plate – bring your swagger.json and start serving.
  • Flexible deployment – run as a CLI, long-lived daemon, or within Docker/Kubernetes.
  • All transport modes –
    • stdio (default).
    • http - StreamableHttp, newest MCP prototcol.
    • sse – self-hosted long-running event source.
  • Pluggable auth – bearer token, basic auth, API keys, OAuth2 or no auth.
  • Runtime configuration – YAML file, CLI flags, or environment variables (prefixed AUTO_MCP_).

🛠️ Using Auto MCP

Easily tailor your Swagger/OpenAPI file for optimal MCP integration. The MCP Config Builder lets you:

  • Edit endpoint descriptions for clearer, more helpful documentation.
  • Filter out unnecessary routes to streamline your API exposure.
  • Preview and customize how endpoints appear to LLMs and clients.
  • Generate an adjustment file (--adjustment-file) for use with Auto MCP, applying your customizations automatically.

MCP Config Builder

How it works
  1. Install the MCP Config Builder:
    go install ./cmd/mcp-config-builder
    
    This will build and install the mcp-config-builder binary to your $GOPATH/bin (usually ~/go/bin). Make sure this directory is in your PATH.
  2. Launch the tool:
    mcp-config-builder --swagger-file=/path/to/swagger.json
    
  3. Interactively review and edit endpoints in a user-friendly TUI (Terminal User Interface).
  4. Save your adjustments to a file for future use or sharing.
  5. Run Auto MCP with your adjustment file to apply your customizations:
    auto-mcp --swagger-file=/path/to/swagger.json --adjustment-file=/path/to/adjustments.json
    

📚 Use Cases

  1. Rapid Prototyping: Wrap any REST API as an MCP server in seconds—ideal for testing ideas or building AI tools fast.

  2. Bridge Legacy Services: Expose legacy or internal systems as MCP endpoints without rewriting them.

  3. Access Any 3rd-Party API from Chat Applications: Turn any third-party API into an MCP tool, making it accessible to AI assistants like Claude.

  4. Minimal Proxy Tools: Use auto-mcp to proxy APIs that already handle validation and logic—no wrappers needed.


🖥️ Running inside Claude Desktop

Add the following snippet to your Claude Desktop configuration (⟂ Settings → MCP Servers):

{
  "mcpServers": {
    "YourMCP": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-v",
        "/Users/you/path/to/swagger.json:/server/swagger.json",
        "ghcr.io/brizzai/auto-mcp:latest"
        "--swagger-file=/server/swagger.json"
      ]
    }
  },
  "globalShortcut": ""
}

Claude will start the container on-demand and connect over STDIO. Replace the host path to swagger.json and image tag to suit your setup.

CLI flags
  • --mode – override server.mode (stdio or sse).
  • --swagger-file – path to the OpenAPI document (default: swagger.json).
  • --adjustment-file - mcp-config-builder output filter/change route descriptions

For detailed configureation guidelines, please see CONFIGURATION.md.


🔐 OAuth Support

Auto MCP supports OAuth 2.1 authentication, including PKCE, dynamic client registration, and multiple providers (internal, GitHub, Google). This allows you to secure your MCP server with industry-standard authentication flows.

See the OAuth Usage Guide for detailed setup instructions, endpoint descriptions, and testing tips.


🐳 Running with Docker

  1. Run in local stdio mode:

    docker run --rm -i \
      -v $(pwd)/swagger.json:/server/swagger.json \
        ghcr.io/brizzai/auto-mcp:latest \
        --swagger-file=/server/swagger.json \
        --mode=stdio
    
  2. Run in remote sse/http mode :

    docker run \
      -v $(pwd)/swagger.json:/server/swagger.json \
        ghcr.io/brizzai/auto-mcp:latest \
        --swagger-file=/server/swagger.json \
        --mode=http
    

The bundled docker-compose.yml maps port 8080 and persists logs to ./logs.

Running the Petshop Example

You can try out the included Petshop demo using Docker. This demo uses a sample configuration and API specs to show how auto-mcp works.

Steps:

  1. Make sure you are in the root directory of this repository.
  2. Run the following command:
docker run --rm -i \
  -v $(pwd)/examples/petshop/config:/config \
  ghcr.io/brizzai/auto-mcp:latest
  • This command mounts the examples/petshop/config directory from your local machine into the Docker container at /config.
  • The /config directory inside the container should contain:
    • config.yaml: Main configuration file for the demo
    • swagger.json: API specification for the Petshop service
    • adjustment.yaml: Optional adjustments or overrides for the API

Note: Any files you place in examples/petshop/config will overwrite the default config.yaml, swagger.json, and adjustment.yaml inside the container.

This setup allows you to easily test and modify the Petshop demo configuration.

See [docs/CONFIGURATION.md](docs/ CONFIGURATION.md) for all config options and environment variable overrides.

🤝 Contributing

For detailed contribution guidelines, please see CONTRIBUTING.md.


📄 License

Distributed under the Apache License 2.0 License. See LICENSE for details.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.