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In today’s newsletter:
5 Powerful MCP Servers.
MCP-Use: Open Source Library to connect any LLM to any MCP server.
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5 Powerful MCP Servers
MCP (Model Context Protocol), an open standard that lets AI models connect to external tools like APIs, databases, file systems, and more, without needing custom code or plugins. Think of it as a universal adapter that gives LLMs access to the outside world.
MCP servers bring this protocol to life. They expose real-world tools in a format LLMs can understand and use directly, with no API docs, no wrappers, and no SDKs. Just connect and run. Your agents can scrape websites, query APIs, sync files, or trigger actions instantly.
Here are the top 5 MCP servers that give superpowers to your AI agents.
Firecrawl let’s you turn entire websites into LLM-ready markdown or structured data. You can Scrape, crawl and extract with a single API.
This MCP server integrates with Firecrawl for web scraping capabilities. You can directly connect this server within your favourite MCP client like Cursor, Windsurf, Goose or Cline.
Key Features:
Scrape, crawl, search, extract, deep research and batch scrape support
Web scraping with JS rendering
URL discovery and crawling
Web search with content extraction
firecrawl MCP
This MCP server enables AI agents to control web browsers using browser-use.
Key Features:
Browser Automation: Control browsers through AI agents
Dual Transport: Support for both SSE and stdio protocols
VNC Streaming: Watch browser automation in real-time
Async Tasks: Execute browser operations asynchronously
browser-use MCP
Opik is an Open source LLM evaluation framework
This MCP Server enables traceability into AI Agents and lets you monitor your LLM applications
Key Features:
Prompts Management: Create, list, update, and delete prompts
Projects/Workspaces Management: Organize and manage projects
Traces: Track and analyze trace data
Metrics: Gather and query metrics data
Opik MCP
Turn any FastAPI app into an MCP server!
FastAPI-MCP is a zero-configuration tool for automatically exposing FastAPI endpoints as Model Context Protocol (MCP) tools.
Key Features:
Direct integration: Mount MCP server to your FastAPI app
Zero configuration: Simply point to your app and it works
Auto discovery: Converts FastAPI endpoints to MCP tools
Swagger docs: Maintains endpoint documentation
Flexible deployment: Mount MCP to the same app or deploy separately
FastAPI MCP
The Github Official MCP server comes with seamless integration with GitHub APIs, enabling advanced automation and interaction capabilities for developers & tools.
Key Features:
One-click Docker installation
Automate GitHub workflows and processes
Extract and analyze data from your repos
Build AI-powered tools that talk directly to GitHub ecosystem
Github MCP
Connect any LLM to any MCP server and build custom AI agents!
MCP-Use is the open source MCP Client Library to connect any LLM to any MCP server and build custom agents with tool access, without relying on closed source or app-specific clients.
Key Features:
🔄 Spin up your first MCP-capable agent in just 6 lines of code
🤖 Works with any LangChain-supported LLM that supports tool use
🌐 Connect directly to MCP servers via HTTP
🧩 Run multiple MCP servers in a single agent
🛡️ Restrict dangerous tools like file system or network access
mcp-use
That’s a Wrap
That’s all for today. Thank you for reading today’s edition. See you in the next issue with more AI Engineering insights.
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