Anthropic Model Context Protocol (MCP)

A Anthropic Model Context Protocol (MCP) is an open-source AI-supporting protocol that enables AI system integration (through standardized interfaces).

• Context:
  • It can (typically) perform Integration Functions through protocol interfaces:
    • Protocol Input: data requests, action commands, configuration settings
    • Protocol Output: retrieved data, action results, status updates
    • Protocol Performance Measure: integration speed, connection reliability, data accuracy
  • ...
  • It can (typically) enable Data Integration through standardized protocols.
  • It can (typically) maintain Bidirectional Communication through protocol channels.
  • It can (typically) support System Interoperability through protocol standards.
  • It can (typically) implement Integration Security through protocol controls.
  • It can (often) provide Server Implementation through TypeScript SDK and Python SDK.
  • It can (often) support Client Development through frontend SDKs and backend SDKs.
  • It can (often) enable Cloud Platform Integration through pre-built servers for Google Drive and Dropbox.
  • It can (often) facilitate Team Collaboration through Slack integration and GitHub integration.
  • It can (often) support Development Testing through protocol inspectors and debug tools.
  • It can (often) provide Implementation Guidance through reference documentation and API specifications.
  • ...
  • It can be developed through Community Contribution.
  • It can be implemented via Protocol SDKs.
  • It can be verified through Protocol Testing.
  • It can maintain Protocol Version state.
  • ...
• Examples:
  • MCP v2024-11-29.
  • ...
• Counter-Examples:
  • Proprietary Integration Protocols, which lack open-source collaboration.
  • One-Way Data Protocols, which lack bidirectional capability.
  • Custom Integration Solutions, which lack standardized interfaces.
• See: Integration Protocol, AI System, Open Source Protocol, Data Integration, Protocol Standard.

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References

2024-11-29

• https://github.com/modelcontextprotocol
  • NOTES:
    • MCP is designed to integrate LLM applications with external data sources and tools, providing a standardized connection protocol.
    • Developers can use the provided TypeScript and Python SDKs to quickly build MCP servers and clients.
    • The project includes a repository of pre-built servers for popular platforms like Google Drive, Slack, and GitHub, making it easier to start.
    • Contributing to MCP is encouraged, with detailed guides and a community forum available to support collaboration.
    • Development tools such as the MCP Inspector and debugging guides facilitate server testing and integration validation.

2024-11-25

• https://www.anthropic.com/news/model-context-protocol
  • QUOTES:
    • "MCP provides a universal, open standard for connecting AI systems with data sources, replacing fragmented integrations with a single protocol."
    • "Open technologies like the Model Context Protocol are the bridges that connect AI to real-world applications, ensuring innovation is accessible, transparent, and rooted in collaboration."
  • NOTES:
    • MCP simplifies AI system integration by eliminating custom connectors for each data source.
    • It supports bidirectional communication, enabling both data retrieval and execution of actions.
    • Pre-built servers for platforms like Slack, GitHub, and Google Drive accelerate deployment.
    • Early adopters, including Block and Apollo, demonstrate MCP’s practical applicability.
    • Open-source architecture fosters collaboration and innovation within the developer community.

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