Python SDK for MCP Mesh — build distributed AI agents with auto-discovery, dependency injection, and LLM integration
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# MCP Mesh Python Runtime Python runtime for the MCP Mesh service mesh framework. ## Installation ```bash pip install mcp-mesh ``` ## Quick Start ```python import mesh # Import types from public API from mesh.types import McpMeshTool # Define your agent @mesh.agent(name="hello-world", http_port=9090) class HelloWorldAgent: """Hello World agent demonstrating MCP Mesh features.""" pass # Create a greeting function with dependency injection @mesh.tool( capability="greeting", dependencies=["date_service"], description="Greeting function with date dependency injection" ) def greet(name: str = "World", date_tool: McpMeshTool = None) -> str: """Greeting function with automatic dependency injection.""" if date_tool is not None: try: current_date = date_tool() return f"Hello, {name}! Today is {current_date}" except Exception: pass return f"Hello, {name}!" # The runtime auto-initializes when you import mcp_mesh # Your functions are automatically registered with the mesh registry ``` ## Features - **Automatic Registration**: Functions are automatically registered with the Go registry - **Health Monitoring**: Built-in health checks and heartbeats - **Dependency Injection**: Inject dependencies into your functions - **Service Discovery**: Find and use other services in the mesh - **Graceful Degradation**: Works even if registry is unavailable ## Configuration The runtime can be configured via environment variables: - `MCP_MESH_ENABLED`: Enable/disable runtime (default: "true") - `MCP_MESH_REGISTRY_URL`: Registry URL (default: "http://localhost:8080") - `MCP_MESH_AGENT_NAME`: Custom agent name (auto-generated if not set) ## API Architecture MCP Mesh uses a clear separation between public and private APIs: - **`mesh`** - Public user API for decorators and types - **`_mcp_mesh`** - Private internal implementation (do not import directly) The underscore prefix on `_mcp_mesh` follo…
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