MCP.so
ログイン

Wikipedia MCP Server

@simakovvv

リポジトリ

Wikipedia MCP Server について

概要はまだありません

#wiki-mcp-server#wikipedia#ai-analysis

基本情報

カテゴリ

メモリとナレッジ

ランタイム

python

トランスポート

stdio

公開者

simakovvv

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "wiki-mcp-server": {
      "command": "python",
      "args": [
        "wiki_mcp_server.py"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

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 Wikipedia MCP Server?

A server for searching and analyzing Wikipedia articles using AI models, accessed via HTTP endpoints and Server-Sent Events.

How to use Wikipedia MCP Server?

Install dependencies with pip install -r requirements.txt, set the OPENROUTER_API_KEY environment variable, then run python wiki_mcp_server.py. The server starts on http://localhost:8000. Use the /search, /evaluate, /analyze, and /stats endpoints with POST or GET requests.

Key features of Wikipedia MCP Server

  • Search Wikipedia articles with AI‑powered relevance scoring.
  • Evaluate a single article’s relevance using an AI model.
  • Analyze article content with AI‑generated insights.
  • Server‑Sent Events (SSE) stream for real‑time search results.
  • Supports multiple AI models: GPT‑3.5‑Turbo, GPT‑4, Claude‑2, Mistral‑7B.
  • Built‑in server statistics and error tracking.

Use cases of Wikipedia MCP Server

  • Automatically retrieve and rank Wikipedia articles on a given topic.
  • Integrate Wikipedia knowledge into AI chatbots or research assistants.
  • Evaluate the relevance of a specific article snippet for a project.
  • Combine article analysis with other MCP tools in an AI pipeline.

FAQ from Wikipedia MCP Server

What API key is required?

The server requires an OpenRouter API key set via the OPENROUTER_API_KEY environment variable.

What AI models are available?

The server supports gpt-3.5-turbo (default), gpt-4, claude-2, and mistral-7b.

How do I run the server?

Install dependencies, export the API key, and run python wiki_mcp_server.py. The server will listen on port 8000.

What endpoints does the server provide?

There are four endpoints: /search (POST, SSE), /evaluate (POST, JSON), /analyze (POST, JSON), and /stats (GET, JSON).

Can I configure server timeouts or connections?

Yes, optional environment variables SERVER_TIMEOUT, KEEPALIVE_TIMEOUT, and MAX_CONNECTIONS can be set.

コメント

「メモリとナレッジ」の他のコンテンツ

Notion MCP Server

suekou

A Model Context Protocol server for connecting Notion to MCP-compatible clients

910

JupyterMCP - Jupyter Notebook Model Context Protocol Integration

jjsantos01

A Model Context Protocol (MCP) for Jupyter Notebook

130

Mcp Knowledge Graph

shaneholloman

MCP server enabling persistent memory for Claude through a local knowledge graph - fork focused on local development

871

Context7 MCP - Up-to-date Docs For Any Cursor Prompt

upstash

Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors

58.7K

MemoryMesh

CheMiguel23

A knowledge graph server that uses the Model Context Protocol (MCP) to provide structured memory persistence for AI models.

348