The Model Context Protocol (MCP) is an open standard that lets AI agents use external tools through a unified interface. Think of it as USB-C for AI — one protocol connects any AI client (Claude Desktop, Cursor, VS Code with Cline) to any tool or data source.
I built three production-ready MCP servers and published them to PyPI and GitHub. Here's what they do and how to use them.
uvx crewai-web-search-mcp
Two tools:
Use cases: Ask your AI about current events, research competitors, pull documentation, verify facts in real time.
{
"mcpServers": {
"web-search": {
"command": "uvx",
"args": ["crewai-web-search-mcp"]
}
}
}
uvx code-review-automation
Three tools:
Use cases: Paste a PR diff and get an instant review. Catch issues before they reach production.
uvx document-intelligence-server
Three tools:
Use cases: Process uploaded PDFs, extract data from scanned forms, summarize long reports.
All three servers use a shared credit system:
| Tier | Price | Credits |
|---|---|---|
| Free | $0 | 50 calls/day |
| Starter | $20 | 2,000 calls |
| Pro | $100 | 12,000 calls |
Buy credits once, use them across any server. Credits never expire.
How it works:
uvx crewai-web-search-mcp
MCP_LICENSE_KEY
→ all limits removedThe billing backend is open source too: github.com/KennyWayn3/mcp-billing-api
pip install crewai-web-search-mcp
What MCP servers would you like to see built next? I'm curious what the community actually needs.