Mcp Serverless

Overview

MCP Serverless is a lightweight, server‑less implementation of the Model Context Protocol (MCP) that focuses on tool management and in‑memory client‑server communication. By abstracting the complexities of a full MCP server, it lets developers expose custom tools—such as calculators, data fetchers, or business logic functions—to AI assistants with minimal setup. The serverless model removes the need for persistent infrastructure, making it ideal for rapid prototyping, edge deployments, or environments where a full HTTP server is overkill.

The core of the package revolves around two complementary components: ToolManager and createService. ToolManager is a registry that stores tool definitions, each comprising a name, description, JSON schema for input validation, and an asynchronous handler function. Once registered, tools can be invoked by name, and the manager automatically validates arguments against their schema before dispatching to the handler. createService builds an in‑memory MCP client and server pair, allowing tools to be called directly from the same process without network latency. This pattern is particularly useful for local testing or embedding MCP logic within a larger application.

Key capabilities include:

• Dynamic tool registration: Add or remove tools at runtime without restarting the server.
• Context propagation: Pass arbitrary context objects (e.g., API keys, user IDs) alongside tool calls, enabling secure and stateful interactions.
• In‑memory transport: Eliminates external dependencies by using a local client-server channel, yet remains fully compatible with the MCP protocol.
• Standard I/O transport examples: Demonstrations of how to hook up the server and client to stdin/stdout, allowing the MCP implementation to be used in CLI workflows or as a subprocess.

Real‑world scenarios that benefit from MCP Serverless include:

• Rapid prototyping: Quickly expose a new set of utilities to an AI assistant during product discovery.
• Edge or offline AI: Run tools locally on devices with limited connectivity, still leveraging MCP’s structured request/response format.
• CI/CD pipelines: Integrate tool calls into automated tests or deployment scripts without spinning up a dedicated server.
• Developer tooling: Build custom IDE extensions that invoke backend logic through MCP, keeping the interface consistent across different environments.

By unifying tool registration, context handling, and lightweight transport in a single package, MCP Serverless empowers developers to extend AI assistants with domain‑specific functionality while keeping the deployment footprint minimal and the integration straightforward.