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🧠 mcp_server-client_EAG-S-4 - Local Setup

@devdastl

🧠 mcp_server-client_EAG-S-4 - Local Setup について

概要はまだありません

基本情報

カテゴリ

その他

ランタイム

python

トランスポート

stdio

公開者

devdastl

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": {
    "local_mcp_server-client_EAG-S-4": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

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 🧠 mcp_server-client_EAG-S-4 - Local Setup?

This repository provides a minimal implementation to set up and interact with the MCP (Modular Computation Protocol) locally. It consists of a server that exposes 28 computational tools and a client that communicates with the server to invoke those tools. The project is managed using the uv Python package manager.

How to use 🧠 mcp_server-client_EAG-S-4 - Local Setup?

Clone the repository, install uv, create a virtual environment, install dependencies from pyproject.toml, then run mcp dev mcp_server.py to test the server or python mcp_client.py to run the client.

Key features of 🧠 mcp_server-client_EAG-S-4 - Local Setup

  • 28 tools including math, string/image, and Pinta automation
  • Uses uv for fast dependency management and reproducibility
  • Server exposes tools that a client can invoke remotely
  • Includes a ready-to-use client entry point
  • Pinta automation tools for drawing rectangles, circles, and text
  • Image thumbnail generation and ASCII conversion tools

Use cases of 🧠 mcp_server-client_EAG-S-4 - Local Setup

  • Perform mathematical calculations via a remote tool server
  • Automate Pinta image editing tasks programmatically
  • Generate thumbnails or convert characters to ASCII values
  • Explore modular computation protocol interactions locally

FAQ from 🧠 mcp_server-client_EAG-S-4 - Local Setup

What does this project do?

It is a minimal implementation of an MCP server and client, allowing a client to call 28 different tools hosted by the server.

What runtime or dependencies are required?

Python 3, uv package manager, and the dependencies listed in pyproject.toml. For Pinta tools, the Pinta application must be installed separately.

How do I run the client?

After setting up the environment, run python mcp_client.py from the project root. The server can be tested with mcp dev mcp_server.py.

Are there any limitations or known caveats?

Pinta automation tools require Pinta to be installed and running. Image tools like create_thumbnail need valid image file paths.

What license is this project under?

MIT License.

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