
APIWeaver
STDIOSTREAMABLE HTTPHTTP-SSEDynamic MCP server that creates AI tools from web API configurations.
Dynamic MCP server that creates AI tools from web API configurations.
A FastMCP server that dynamically creates MCP (Model Context Protocol) servers from web API configurations. This allows you to easily integrate any REST API, GraphQL endpoint, or web service into an MCP-compatible tool that can be used by AI assistants like Claude.
APIWeaver supports three different transport types to accommodate various deployment scenarios:
apiweaver run
or apiweaver run --transport stdio
apiweaver run --transport sse --host 127.0.0.1 --port 8000
http://host:port/mcp
apiweaver run --transport streamable-http --host 127.0.0.1 --port 8000
http://host:port/mcp
# Clone or download this repository cd ~/Desktop/APIWeaver # Install dependencies pip install -r requirements.txt
{ "mcpServers": { "apiweaver": { "command": "uvx", "args": ["apiweaver", "run"] } } }
There are several ways to run the APIWeaver server with different transport types:
1. After installation (recommended):
If you have installed the package (e.g., using pip install .
from the project root after installing requirements):
# Default STDIO transport apiweaver run # Streamable HTTP transport (recommended for web deployments) apiweaver run --transport streamable-http --host 127.0.0.1 --port 8000 # SSE transport (legacy compatibility) apiweaver run --transport sse --host 127.0.0.1 --port 8000
2. Directly from the repository (for development):
# From the root of the repository python -m apiweaver.cli run [OPTIONS]
Transport Options:
--transport
: Choose from stdio
(default), sse
, or streamable-http
--host
: Host address for HTTP transports (default: 127.0.0.1)--port
: Port for HTTP transports (default: 8000)--path
: URL path for MCP endpoint (default: /mcp)Run apiweaver run --help
for all available options.
APIWeaver is designed to expose web APIs as tools for AI assistants that support the Model Context Protocol (MCP). Here's how to use it:
Start the APIWeaver Server:
For modern MCP clients (recommended):
apiweaver run --transport streamable-http --host 127.0.0.1 --port 8000
For legacy compatibility:
apiweaver run --transport sse --host 127.0.0.1 --port 8000
For local desktop applications:
apiweaver run # Uses STDIO transport
Configure Your AI Assistant: The MCP endpoint will be available at:
http://127.0.0.1:8000/mcp
http://127.0.0.1:8000/mcp
Register APIs and Use Tools:
Once connected, use the built-in register_api
tool to define web APIs, then use the generated endpoint tools.
The server provides these built-in tools:
{ "name": "my_api", "base_url": "https://api.example.com", "description": "Example API integration", "auth": { "type": "bearer", "bearer_token": "your-token-here" }, "headers": { "Accept": "application/json" }, "endpoints": [ { "name": "list_users", "description": "Get all users", "method": "GET", "path": "/users", "params": [ { "name": "limit", "type": "integer", "location": "query", "required": false, "default": 10, "description": "Number of users to return" } ] } ] }
{ "name": "weather", "base_url": "https://api.openweathermap.org/data/2.5", "description": "OpenWeatherMap API", "auth": { "type": "api_key", "api_key": "your-api-key", "api_key_param": "appid" }, "endpoints": [ { "name": "get_current_weather", "description": "Get current weather for a city", "method": "GET", "path": "/weather", "params": [ { "name": "q", "type": "string", "location": "query", "required": true, "description": "City name" }, { "name": "units", "type": "string", "location": "query", "required": false, "default": "metric", "enum": ["metric", "imperial", "kelvin"] } ] } ] }
{ "name": "github", "base_url": "https://api.github.com", "description": "GitHub REST API", "auth": { "type": "bearer", "bearer_token": "ghp_your_token_here" }, "headers": { "Accept": "application/vnd.github.v3+json" }, "endpoints": [ { "name": "get_user", "description": "Get a GitHub user's information", "method": "GET", "path": "/users/{username}", "params": [ { "name": "username", "type": "string", "location": "path", "required": true, "description": "GitHub username" } ] } ] }
{ "auth": { "type": "bearer", "bearer_token": "your-token-here" } }
{ "auth": { "type": "api_key", "api_key": "your-key-here", "api_key_header": "X-API-Key" } }
{ "auth": { "type": "api_key", "api_key": "your-key-here", "api_key_param": "api_key" } }
{ "auth": { "type": "basic", "username": "your-username", "password": "your-password" } }
{ "auth": { "type": "custom", "custom_headers": { "X-Custom-Auth": "custom-value", "X-Client-ID": "client-123" } } }
?param=value
)/users/{id}
){ "timeout": 60.0 // Timeout in seconds }
{ "name": "status", "type": "string", "enum": ["active", "inactive", "pending"] }
{ "name": "page", "type": "integer", "default": 1 }
{ "mcpServers": { "apiweaver": { "command": "apiweaver", "args": ["run", "--transport", "streamable-http", "--host", "127.0.0.1", "--port", "8000"] } } }
{ "mcpServers": { "apiweaver": { "command": "apiweaver", "args": ["run"] } } }
The server provides detailed error messages for:
streamable-http
for modern deployments, stdio
for local toolstest_api_connection
after registering an APIRun with verbose logging (if installed):
apiweaver run --verbose
Feel free to extend this server with additional features:
MIT License - feel free to use and modify as needed.