Architecture overview

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Scope

• MCP Specification: A specification of MCP that outlines the implementation requirements for clients and servers.
• MCP SDKs: SDKs for different programming languages that implement MCP.
• MCP Development Tools: Tools for developing MCP servers and clients, including the MCP Inspector
• MCP Reference Server Implementations: Reference implementations of MCP servers.

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Concepts of MCP

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Participants

• MCP Host: The AI application that coordinates and manages one or multiple MCP clients
• MCP Client: A component that maintains a connection to an MCP server and obtains context from an MCP server for the MCP host to use
• MCP Server: A program that provides context to MCP clients

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Layers

• Data layer: Defines the JSON-RPC based protocol for client-server communication, including capability and version discovery, and core primitives, such as tools, resources, prompts and notifications.
• Transport layer: Defines the communication mechanisms and channels that enable data exchange between clients and servers, including transport-specific connection establishment, message framing, and authorization.

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Data layer

• Discovery: Lets clients query a server’s supported protocol versions, capabilities, and identity through the server/discover request
• Server features: Enables servers to provide core functionality including tools for AI actions, resources for context data, and prompts for interaction templates from and to the client
• Client features: Enables servers to elicit input from the user. Sampling is deprecated as of protocol version 2026-07-28.
• Utility features: Supports additional capabilities like notifications for real-time updates and progress tracking for long-running operations

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Transport layer

• Stdio transport: Uses standard input/output streams for direct process communication between local processes on the same machine, providing optimal performance with no network overhead.
• Streamable HTTP transport: Uses HTTP POST for client-to-server messages with optional Server-Sent Events for streaming capabilities. This transport enables remote server communication and supports standard HTTP authentication methods including bearer tokens, API keys, and custom headers. MCP recommends using OAuth to obtain authentication tokens.

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Data Layer Protocol

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Statelessness and discovery

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Primitives

• Tools: Executable functions that AI applications can invoke to perform actions (e.g., file operations, API calls, database queries)
• Resources: Data sources that provide contextual information to AI applications (e.g., file contents, database records, API responses)
• Prompts: Reusable templates that help structure interactions with language models (e.g., system prompts, few-shot examples)

• Elicitation: Allows servers to request additional information from users. This is useful when server authors want to get more information from the user, or ask for confirmation of an action. Servers request user input with the elicitation/create method.

• Sampling: Allows servers to request language model completions from the client’s AI application. This is useful when server authors want access to a language model, but want to stay model-independent and not include a language model SDK in their MCP server. Servers request completions with the sampling/createMessage method, also delivered through the Multi Round-Trip Requests pattern. New implementations should integrate directly with LLM provider APIs.
• Logging: Enables servers to send log messages to clients for debugging and monitoring purposes. New implementations should log to stderr (stdio transport) or use OpenTelemetry.

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Notifications

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Example

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Data Layer

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "server/discover",
  "params": {
    "_meta": {
      "io.modelcontextprotocol/protocolVersion": "2026-07-28",
      "io.modelcontextprotocol/clientInfo": {
        "name": "example-client",
        "version": "1.0.0"
      },
      "io.modelcontextprotocol/clientCapabilities": {
        "elicitation": {}
      }
    }
  }
}

{
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "resultType": "complete",
    "supportedVersions": ["2026-07-28"],
    "capabilities": {
      "tools": {
        "listChanged": true
      },
      "resources": {}
    },
    "_meta": {
      "io.modelcontextprotocol/serverInfo": {
        "name": "example-server",
        "version": "1.0.0"
      }
    },
    "ttlMs": 3600000,
    "cacheScope": "public"
  }
}

# Pseudo Code
async with Client(stdio_client(server_config)) as client:
    if client.server_capabilities.tools:
        app.register_mcp_server(client, supports_tools=True)
    app.set_server_ready(client)