What is mcp_starter_cli used for?
mcp_starter_cli is a CLI tool for scaffolding, running, and testing MCP servers locally with Node.js or Python, and supports API key injection and Claude Desktop integration.
@Sumedh1599
基本信息
CLI tool to scaffold, run, and test MCP servers locally with Node.js or Python, integrated with Claude and OpenAI key injection and auto-link to Claude Desktop.
工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
mcp_starter_cli is a command line interface tool for scaffolding, running, and testing MCP servers locally using Node.js or Python. It integrates with OpenAI and Claude API keys and supports automatic linking to Claude Desktop for local agent testing.
Install globally via npm install -g mcp_starter_cli or yarn global add mcp_starter_cli. Use mcp_starter_cli scaffold to create a new project, mcp_starter_cli run to start the server, mcp_starter_cli config set to inject API keys, and mcp_starter_cli logs to monitor server logs in real time.
mcp_starter_cli is a CLI tool for scaffolding, running, and testing MCP servers locally with Node.js or Python, and supports API key injection and Claude Desktop integration.
You need Node.js installed on your system. No other runtime is required by default, though using Python templates requires Python.
Install it globally using npm: `npm install -g mcp_starter_cli`, or with Yarn: `yarn global add mcp_starter_cli`.
Yes, use `mcp_starter_cli config set openai-key YOUR_KEY` for OpenAI or `mcp_starter_cli config set claude-key YOUR_KEY` for Claude.
Yes, you can scaffold a Python project with `mcp_starter_cli scaffold my-project --template python` and run it with `mcp_starter_cli run`.
Query your team's drift, vulnerability, and migration data from any AI assistant. Vibgrate MCP connects Cursor, Claude, ChatGPT, Windsurf, or VS Code to Vibgrate Cloud: 51 tools for DriftScores, CVEs and EOL runtimes, up

Verified distributed compute for humans, applications, and agents. Submit Blender, Octane, and video workloads, route them across qualified GPUs, track asynchronous execution, download finished artifacts, and verify FARP

Automated codebase documentation for GitHub: searchable docs, MCP context for AI agents, doc drift detection, and Friday Cleanup PRs.

MCP-first toolbox for agents: namespaced key-value storage, a FIFO queue, auth, and a handful of stateless utility tools (JWT decode, hashing, cert inspection, CIDR math). Free while in early access. This repository is a
OrangePro local-first CLI + MCP server for behavior mapping, grounded test generation, and dynamic proof.
评论