Model Context Protocol

A universal standard for AI-human collaboration. Clean, functional, and built for the future.

Core Features

Tools

Standardized tool interfaces for AI systems to interact with external services and data sources.

Resources

Efficient resource management and data access patterns for seamless AI integration.

Prompts

Dynamic prompt templates and context management for enhanced AI interactions.

Technical Specifications

Protocol Foundation

Built on JSON-RPC 2.0 for reliable, standardized communication between AI systems and external services.

Transport Agnostic

Works across multiple transport layers including WebSockets, HTTP, and stdio for maximum flexibility.

Open Standard

Fully open specification with reference implementations in multiple programming languages.

View Full Specification

Architecture Layers

  • Application: MCP Client/Server
  • Protocol: JSON-RPC 2.0
  • Transport: WebSocket/HTTP/stdio

Code Examples

Server Implementation

const server = new Server({ name: "my-tools", version: "1.0.0" }); server.setRequestHandler( ListToolsRequestSchema, async () => ({ tools: [{ name: "calculate", description: "Math operations", inputSchema: { type: "object", properties: { operation: { type: "string" }, values: { type: "array" } } } }] }) );

Client Connection

const client = new Client({ name: "my-app", version: "1.0.0" }); await client.connect(transport); const result = await client.request({ method: "tools/call", params: { name: "calculate", arguments: { operation: "add", values: [1, 2] } } });

Documentation

Getting Started

Quick start guide to implementing MCP in your application with step-by-step instructions.

Start Building

SDK Support

Official SDKs available for TypeScript, Python, and Go with comprehensive documentation.

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Community

Join the MCP community for support, examples, and contributions to the protocol.

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Get Started with MCP

Choose your platform and start building with the Model Context Protocol today.