MCPStudio: The Postman for Model Context Protocol

Name: MCPStudio: The Postman for Model Context Protocol
Author: lonexreb

@lonexreb

リポジトリ

MCPStudio: The Postman for Model Context Protocol について

Postman for MCP servers

基本情報

カテゴリ

その他

ランタイム

node

トランスポート

stdio

公開者

lonexreb

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": {
    "MCPstudio": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv",
        "&&",
        "source",
        "venv/bin/activate",
        "#",
        "Windows:",
        "venvScriptsactivate"
      ]
    }
  }
}

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 MCPStudio?

MCPStudio is a web platform for creating, testing, managing, and discovering Model Context Protocol (MCP) servers. Like Postman for APIs, it provides a visual interface that abstracts away protocol complexity, allowing users to connect to MCP servers, discover tools, execute them with parameters, and inspect results—all from the browser.

How to use MCPStudio?

Clone the repository, then install and run the backend (Python 3.10+ with UV) and frontend (Node.js 16+ with npm). Open http://localhost:8080, sign up or log in, and start managing MCP servers. The guided onboarding tour helps you get started.

Key features of MCPStudio

Server creation, configuration, and connection with status tracking
Auto-discovery and execution of MCP tools via dynamic forms
Visual pipeline builder with drag-and-drop DAG canvas
Tool Execution Arena for side-by-side comparison with JSON diff
MCP server discovery from npm and GitHub registries
Supabase authentication with email/password and OAuth2 for Google Drive

Use cases of MCPStudio

Developers prototyping and testing MCP server integrations
Data scientists chaining MCP tools into reusable pipelines
Teams collaborating on MCP tool execution and configuration
Discovering and evaluating MCP-compatible servers from the community

FAQ from MCPStudio

What are the runtime requirements for MCPStudio?

Python 3.10+, Node.js 16+, and optionally MongoDB (falls back to in-memory mock). The UV package manager is recommended for the backend.

How does authentication work?

MCPStudio uses Supabase email/password signup and login with JWT tokens. It also supports OAuth2 flows for service integrations like Google Drive.

Where is execution history and user data stored?

Execution history, pipeline definitions, and prompt templates are stored in IndexedDB (via Dexie) on the client side. The backend uses MongoDB (or in-memory mock) for persistent server-side logs. Zustand state is persisted to localStorage.