Overview

MCP Runner is a Rust library that turns your application into a lightweight orchestrator for Model Context Protocol (MCP) servers. It tackles the common pain point of managing multiple MCP services—each potentially running in a different runtime or container—by providing a single, type‑safe interface to start, stop, and interact with those servers locally. For developers building AI assistants that need to tap into external capabilities—such as web‑fetching, file I/O, or custom data pipelines—MCP Runner eliminates the boilerplate of spawning processes, handling inter‑process communication, and exposing Server‑Sent Events (SSE) for real‑time updates.

The core value of MCP Runner lies in its unified server lifecycle management. By declaring servers in a JSON configuration, you can launch an arbitrary number of MCP services with a single command. The library automatically constructs the necessary JSON‑RPC client stubs, handles authentication, and even sets up an optional SSE proxy that forwards event streams from the servers to your client application. This means you can treat each MCP service as a first‑class citizen in your codebase, calling tools or querying resources without worrying about transport details.

Key capabilities include:

• Process orchestration: Start, stop, and monitor multiple MCP servers from a single Rust process.
• JSON‑RPC communication: Seamlessly call , , and resource endpoints with strongly‑typed request/response handling.
• SSE proxying: Expose a single HTTP endpoint that aggregates event streams from chosen servers, simplifying client integration.
• Configuration flexibility: Load server definitions from files, strings, or programmatic structures, supporting environment variables and custom command arguments.
• Observability: Integrated with the ecosystem, allowing fine‑grained logging of server lifecycle events and RPC traffic.

In practice, developers use MCP Runner in scenarios such as building a local AI assistant that needs to browse the web, manipulate files, or query internal APIs. By spinning up dedicated MCP servers for each capability, the assistant can delegate tasks to specialized tools while maintaining a clean, modular architecture. The SSE proxy is especially useful for real‑time streaming responses—like long‑running data fetches or live updates—to the assistant’s front end.

Overall, MCP Runner offers a pragmatic bridge between Rust applications and the MCP ecosystem. It abstracts away process management and networking complexities, letting developers focus on designing AI workflows that leverage external tools in a reliable, observable manner.