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MCP (Model Context Protocol) is an open-source standard for connecting AI applications to external systems.

概要

MCP (Model Context Protocol) is an open-source standard for connecting AI applications to external systems. MCP introducted by Anthropic in November 2024, adopted by many AI companies including Google, OpenAI, Microsoft, etc. Using MCP, AI application like Claude, ChatGPT, Gemini,etc can connect and access datasources (local files, databases) and tools like (search engines, fetching external, APIs) and workflows (e.g. specialized prompts) enabling them to access key information and perform tasks. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect electronic devices, MCP provides a standardized way to connect AI applications to external systems. 1. Agents can access your Google Calendar and Notion, acting as a more personalized AI assistant by using MCP. 2. Enterprise chatbots can connect to multiple databases across an organization, empowering users to analyze data using chat. 3.

README

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What is the Model Context Protocol (MCP)?

MCP (Model Context Protocol) is an open-source standard for connecting AI applications to external systems. MCP introducted by Anthropic in November 2024, adopted by many AI companies including Google, OpenAI, Microsoft, etc. Using MCP, AI application like Claude, ChatGPT, Gemini,etc can connect and access datasources (local files, databases) and tools like (search engines, fetching external, APIs) and workflows (e.g. specialized prompts) enabling them to access key information and perform tasks.

Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect electronic devices, MCP provides a standardized way to connect AI applications to external systems.

What can MCP enable?

  1. Agents can access your Google Calendar and Notion, acting as a more personalized AI assistant by using MCP.
  2. Enterprise chatbots can connect to multiple databases across an organization, empowering users to analyze data using chat.
  3. Access external data — read files, databases, Google Drive, Notion, etc.
  4. Use tools — search the web, run code, query APIs
  5. Take actions — send emails, create calendar events, manage tasks
  6. Connect to local systems — interact with your file system, terminal, or local apps
  7. Integrate services — GitHub, Postgres,and social media accounts like whatsapp, instagram, facebook, twitter, etc.

Why does MCP matter?

Depending on where you sit in the ecosystem, MCP can have a range of benefits.

  • Developers: MCP reduces development time and complexity when building, or integrating with, an AI application or agent.
  • AI applications or agents: MCP enables AI applications or agents to access external systems and tools, allowing them to perform tasks that they would not be able to perform on their own.
  • Businesses: MCP enables businesses to integrate their AI applications with their existing systems, allowing them to leverage the power of AI to improve their operations.
  • Users: MCP enables users to access the power of AI to improve their lives, allowing them to perform tasks that they would not be able to perform on their own.

MCP Architecture

Concepts of MCP

1. Participants:

MCP follows a client-server architecture where an MCP host establish connection between one or more MCP servers. The MCP host accomplishes this by creating one MCP client for each MCP server. Each MCP client maintains a dedicated connection with its corresponding MCP server. Local MCP servers that use the STDIO (Standard Input/Output) transport typically serve a single MCP client, whereas remote MCP servers that use the Streamable HTTP transport will typically serve many MCP clients.

    - **Key Participants**: 
    The key participants in the MCP architecture are:
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インストール

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