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MCP Knowledge Base

@gmogmzGithub

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基本情報

カテゴリ

AI とエージェント

トランスポート

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作者

gmogmzGithub

MCP Knowledge Base について

A lightweight knowledge base assistant using MCP with LLM integration. Features a streamlined server-client architecture combining custom tools with a knowledge base, all accessible via SSE transport. Ideal for building simple AI-powered knowledge assistants.

MCP Knowledge Base の設定

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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。

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MCP Knowledge Base のツール

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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?

A simple MCP client‑server application that uses OpenAI to answer questions from a built‑in knowledge base. It is intended for learning the MCP protocol or building a custom Q&A system.

How to use MCP Knowledge Base?

Install dependencies with Poetry, set your OpenAI API key in a .env file, start the server via poetry run python server.py, and run the client with poetry run python client-sse.py. The client offers two modes: direct tool calls (uncomment the test line) or LLM‑powered interactions that interpret natural‑language queries.

Key features of MCP Knowledge Base

  • MCP server exposing tools via decorators
  • MCP client with LLM query interpretation
  • Knowledge base stored in data/kb.json
  • Direct tool‑call mode for testing
  • LLM‑powered mode for natural‑language questions

Use cases of MCP Knowledge Base

  • Learn the MCP client‑server architecture interactively
  • Build a domain‑specific Q&A system with a custom knowledge base
  • Prototype tool calls with or without an LLM orchestrator

よくある質問

1

What are the runtime requirements?

Python 3.9 or higher, Poetry for dependency management, and a valid OpenAI API key.

2

How do I change the knowledge base content?

Edit the `data/kb.json` file with the Q&A pairs you want to use.

3

How do I add a new server tool?

Define a new Python function decorated with `@mcp.tool()` inside `server.py`.

4

How do I run the client without an LLM?

Uncomment the `asyncio.run(test_direct_tool_calls())` line in `client-sse.py` to call tools directly.

5

How do I change the LLM model used?

Modify the `model` parameter in the `MCPClient` initialization inside `client-sse.py`.

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