Model Context Protocol (MCP) Schema for Rust

A type-safe Rust implementation of the official Model Context Protocol (MCP) schema, supporting all official MCP Protocol versions:

• 2026-07-28 (default)
• 2025-11-25
• 2025-06-18
• 2025-03-26
• 2024-11-05
• draft

The MCP schemas in this repository are automatically generated from the official Model Context Protocol, ensuring they are always up-to-date and aligned with the latest official specifications.

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Note: This crate only provides an implementation of the MCP schema.

If you are looking for a high-performance, asynchronous toolkit for building MCP servers and clients, checkout rust-mcp-sdk. Focus on your app's logic while rust-mcp-sdk takes care of the rest!

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Contents:

• Features

• How can this crate be used?

• Schema Versions

  • How to switch between different schema versions?
  • How are Schemas generated?

• What is schema_utils?

• What does the schema_utils do?

• Usage Examples

  • Detecting a CallToolRequest Message on an MCP Server
  • Creating a CallToolResult Response on an MCP Server
  • Detecting a CallToolResult Response Message in an MCP Client

• Usage Examples (Without Utilizing schema_utils)

  • Detecting a CallToolRequest Message on an MCP Server (without schema_utils)

• Contributing

Features

• 🧩 Type-safe implementation of the MCP protocol specification.
• 💎 Auto-generated schemas are always synchronized with the official schema specifications.
• 📜 Includes all official released versions : 2026-07-28, 2025-11-25, 2025-06-18, 2025-03-26, 2024-11-05 and draft version for early adoption.
• 🛠 Complimentary schema utility module (schema_utils) to boost productivity and ensure development integrity.

How can this crate be used?

This Crate provides Rust implementation of the official Model Context Protocol (MCP) schema.

Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need.

This crate includes the schema with serialization / deserialization support via serde_json, along with a minimal implementation of the necessary traits for structs and enums. This helps in creating and using various MCP messages such as requests, responses, notifications, and errors.