mcp-creator

Scaffold, test, and package Model Context Protocol servers for APIs, websites, and portals.

Updated Sep 17, 2026
One-click install
npx skills add https://github.com/tanujkumar38/unified-mcp-gateway --skill mcp-creator-tanujkumar38
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: mcp-creator
Source: https://github.com/tanujkumar38/unified-mcp-gateway/tree/main/.agents/skills/mcp-creator
Command: npx skills add https://github.com/tanujkumar38/unified-mcp-gateway --skill mcp-creator-tanujkumar38

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve? Building a Model Context Protocol server that works across Claude Desktop, ChatGPT, Cursor, and other AI hosts requires navigating transport differences, protocol handshake rules, stdout hygiene, and platform-specific restrictions, which this Skill codifies into a repeatable engineering workflow. ## Core Features & Use Cases - Automated Scaffolding: Generate complete MCP server projects via scripts/mcp_scaffold.py for universal, gateway, TypeScript stdio/HTTP, Python FastMCP, private-API, and browser-automation archetypes. - Protocol Verification: Validate handshake, ping, tool discovery, and stdout pollution automatically with scripts/verify_mcp_server.py. - Platform & Scaling Guidance: Reference playbooks cover ChatGPT Connectors (search/fetch tools, readOnlyHint), dual stdio/HTTP transports, and the 4-tool Meta-Tool gateway pattern that cuts context usage by roughly 97%. - Use Case: Connect an internal enterprise portal with no public API to Claude Desktop by scaffolding a private-api server, implementing session re-authentication, and verifying it with the protocol tester before registering it in claude_desktop_config.json. ## Quick Start Ask the agent to use the mcp-creator skill to scaffold a universal MCP server for your target service and verify it with the protocol tester.

Frequently Asked Questions about mcp-creator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build an MCP server for a website without an API?

Choose one of three archetypes based on the target: web scraping with Axios and Cheerio for public read-only content, Puppeteer browser automation for JavaScript-heavy interactive sites, or private-API reverse engineering of internal XHR endpoints for authenticated portals. The scaffolding script generates a starter project for each archetype.

How to make an MCP server work with ChatGPT?

ChatGPT requires a remote HTTPS SSE endpoint and does not support local stdio transport. Expose standardized search and fetch tools, set readOnlyHint: true on all read operations to avoid approval prompts, wrap Resources and Prompts as callable tools, and tunnel the server via ngrok or Cloudflare Tunnel.

Why does my MCP server fail with JSON parsing errors in Claude Desktop?

The most common cause is stdout pollution: any console.log or print writing to stdout corrupts the JSON-RPC 2.0 stream in stdio transport. Route all diagnostic logging to stderr, then verify with the MCP Inspector or the verify_mcp_server.py script which detects non-JSON stdout output.

What is the Meta-Tool pattern for MCP gateways?

The Meta-Tool pattern registers only four tools (list_plugins, search_tools, get_tool_schema, call_tool) instead of exposing every upstream tool schema. This reduces context consumption from roughly 40,000 tokens to about 1,200 tokens when aggregating 50-100+ tools across multiple servers.

Should I use stdio or HTTP transport for an MCP server?

Use stdio for local desktop clients like Claude Desktop, Cursor, and VS Code since it needs no network ports and runs as a 1:1 subprocess. Use Streamable HTTP with SSE for remote clients, ChatGPT, or shared team infrastructure, with HTTPS and Bearer token authentication enforced.

What are the limitations of browser automation MCP servers?

Browser automation has high latency (5-30 seconds), lower reliability due to DOM changes and timing issues, and struggles with MFA or CAPTCHA challenges. It is best suited for prototyping; private-API reverse engineering offers faster, more stable production integration when endpoints can be captured.