広告掲載
MCP.so
ログイン

MCP Knowledge Base

@EXPESRaza

リポジトリ

基本情報

カテゴリ

メモリとナレッジ

ライセンス

MIT

トランスポート

stdio

作者

EXPESRaza

MCP Knowledge Base について

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

MCP Knowledge Base の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

MCP Knowledge Base のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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

よくある質問

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.

コメント

「メモリとナレッジ」の他のコンテンツ

Neither MCP

stonianua

Project context your AI can query through MCP — with source evidence.

server-noonien - shared memory MCP

sequico

Shared, serverless, conflict-free memory for AI agents: a multi-machine drop-in for the MCP memory knowledge graph.

Sooveryn

PANDAPROG

Sooveryn gives Claude Code a team of AI personas that remembers your project. Soov, the partner and team lead, keeps your decisions and how you work in a lasting memory, and finds them again by words and by meaning, from

Takibi Base

Deian Isac

Ask your Takibi Base collections anything; get answers with cited passages and a support score.

Scento Perfume API (MCP server): free fragrance API, no key

Scento

Scento Perfume API is a free fragrance API and perfume notes database for developers and AI agents. Search 1,500+ perfumes and 400+ ingredients, compare scents, find similar perfumes, map scent families and build occasio

広告掲載