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MCP Knowledge Base

@EXPESRaza

代码仓库

基本信息

分类

记忆与知识

许可证

MIT

传输方式

stdio

作者

EXPESRaza

关于 MCP Knowledge Base

A knowledge base and experimental playground for exploring the Model Context Protocol (MCP)—understanding how hosts, servers, LLMs, and tools interact.

MCP Knowledge Base 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块，请前往代码仓库查看安装说明。

代码仓库

MCP Knowledge Base 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP Knowledge Base?

MCP Knowledge Base is a personal and public repository that explains the Model Context Protocol (MCP) — an emerging standard for enabling LLMs to call tools via structured interactions. It is intended for learners and explorers of MCP, providing explanations, diagrams, sample Python code, and notes.

How to use MCP Knowledge Base?

Browse the repository and explore the examples/, notes/, diagrams/, and schemas/ folders. The README describes planned sample scripts in examples/ that simulate MCP host-server communication and tool invocation.

Key features of MCP Knowledge Base

  • Explanations of MCP communication flow
  • Diagrams showing interactions between host, server, LLM, and tools
  • Sample Python code simulating the MCP pipeline
  • Notes and references to papers or discussions
  • Exploration of toolchains, caching, and state management in MCP

Use cases of MCP Knowledge Base

  • Understand how the Model Context Protocol works from user input to final output
  • Study tool discovery, execution, and result handling in an MCP setup
  • Reference a structured summary of MCP concepts (tools, host, server, schemas, context handling)
  • Get started with minimal Python examples of an MCP pipeline

常见问题

1

What is the Model Context Protocol (MCP)?

MCP is an emerging standard that enables LLMs to call tools via structured interactions between a host, server, and LLM.

2

How does MCP work in this knowledge base?

The lifecycle includes user input, tool discovery, query dispatch, tool selection by the LLM, tool execution via the server, result handling, and final output.

3

Are there working code examples in this repository?

The README states that examples like `basic_mcp_demo.py`, `tool_plugin_example.py`, and `mcp_host_server_flow.py` will be added to the `examples/` folder.

4

What dependencies or runtime are needed?

The README does not specify any required dependencies or runtime environments.

5

Where is the official MCP specification referenced?

References to LangChain's tool calling, OpenAI's Function Calling, and future MCP spec links are mentioned; specific spec links are to be added.

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