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docs/_index.md

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---
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title: Model Context Protocol Specification
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title: Specification
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type: docs
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weight: 1
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---
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The following is the formal specification of the Model Context Protocol, and aims
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to be a resource for implementors.
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{{< callout type="info" >}}
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**Protocol Revision**: 2024-11-05 (Final)
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{{< /callout >}}
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The 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 specification defines the authoritative protocol requirements based on the TypeScript schema in [schema.ts](https://github.com/modelcontextprotocol/specification/blob/main/schema/schema.ts). For implementation guides and examples, visit [modelcontextprotocol.io](https://modelcontextprotocol.io).
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## Overview
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MCP provides a standardized way for applications to:
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- Share contextual information with language models
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- Expose tools and capabilities to AI systems
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- Build composable integrations and workflows
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The protocol uses JSON-RPC 2.0 messages to establish communication between:
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- **Clients**: Applications that integrate with language models
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- **Servers**: Services that provide context and capabilities
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- **Hosts**: Processes that manage client connections
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## Core Protocol Features
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MCP defines several key components:
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### Base Protocol
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- JSON-RPC message format
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- Capability negotiation
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- Session lifecycle management
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### Context Primitives
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- **Resources**: Data exposed via URIs
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- **Prompts**: Template-based interactions
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- **Tools**: Executable functions
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- **Sampling**: LLM generation control
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### Cross-Cutting Concerns
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- Progress tracking
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- Error handling
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- Security boundaries
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- Backwards compatibility
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## Learn More
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Explore the detailed specification for each protocol component:
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{{< cards >}}
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{{< card link="architecture" title="Architecture" icon="template" >}}
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{{< card link="basic" title="Base Protocol" icon="code" >}}
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{{< card link="server" title="Server Features" icon="server" >}}
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{{< card link="client" title="Client Features" icon="user" >}}
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{{< card link="contributing" title="Contributing" icon="pencil" >}}
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{{< /cards >}}
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For a user guides and SDK configuration, plesae visit https://modelcontextprotocol.io.

docs/documentation/_index.md

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---
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title: "User Documentation"
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weight: 20
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---
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The Model Context Protocol (MCP) provides multiple resources for documentation and implementation:
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- **User Documentation**: Visit [modelcontextprotocol.io](https://modelcontextprotocol.io) for comprehensive user-facing documentation
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- **Python SDK**: The Python implementation is available at [github.com/modelcontextprotocol/python-sdk](https://github.com/modelcontextprotocol/python-sdk) - [Discussions](https://github.com/modelcontextprotocol/python-sdk/discussions)
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- **Specification**: The core specification is available at [github.com/modelcontextprotocol/specification](https://github.com/modelcontextprotocol/specification) - [Discussions](https://github.com/modelcontextprotocol/specification/discussions)
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- **TypeScript SDK**: The TypeScript implementation can be found at [github.com/modelcontextprotocol/typescript-sdk](https://github.com/modelcontextprotocol/typescript-sdk) - [Discussions](https://github.com/modelcontextprotocol/typescript-sdk/discussions)
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For questions or discussions, please open a discussion in the appropriate GitHub repository based on your implementation or use case. You can also visit the [Model Context Protocol organization on GitHub](https://github.com/modelcontextprotocol) to see all repositories and ongoing development.

docs/specification/_index.md

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---
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title: Specification
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cascade:
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type: docs
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weight: 10
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---
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{{< callout type="info" >}}
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**Protocol Revision**: 2024-11-05 (Final)
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{{< /callout >}}
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The 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 specification defines the authoritative protocol requirements based on the TypeScript schema in [schema.ts](https://github.com/modelcontextprotocol/specification/blob/main/schema/schema.ts). For implementation guides and examples, visit [modelcontextprotocol.io](https://modelcontextprotocol.io).
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## Overview
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MCP provides a standardized way for applications to:
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- Share contextual information with language models
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- Expose tools and capabilities to AI systems
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- Build composable integrations and workflows
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The protocol uses JSON-RPC 2.0 messages to establish communication between:
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- **Clients**: Applications that integrate with language models
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- **Servers**: Services that provide context and capabilities
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- **Hosts**: Processes that manage client connections
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## Core Protocol Features
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MCP defines several key components:
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### Base Protocol
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- JSON-RPC message format
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- Capability negotiation
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- Session lifecycle management
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### Context Primitives
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- **Resources**: Data exposed via URIs
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- **Prompts**: Template-based interactions
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- **Tools**: Executable functions
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- **Sampling**: LLM generation control
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### Cross-Cutting Concerns
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- Progress tracking
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- Error handling
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- Security boundaries
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- Backwards compatibility
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## Learn More
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Explore the detailed specification for each protocol component:
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{{< cards >}}
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{{< card link="architecture" title="Architecture" icon="template" >}}
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{{< card link="basic" title="Base Protocol" icon="code" >}}
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{{< card link="server" title="Server Features" icon="server" >}}
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{{< card link="client" title="Client Features" icon="user" >}}
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{{< card link="contributing" title="Contributing" icon="pencil" >}}
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{{< /cards >}}
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