April 21, 2025

5 Open-Source MCP Servers That ll Make Your AI Agents Unstoppable

So, I've been messing around with AI lately — Claude, mostly — and I got kinda bored with it just answering questions.

I wanted it to do stuff, you know? Like pull data from websites or poke around my GitHub.

That's when I found these things called MCP servers. They're like little helpers that let your AI interact with tools and apps. Open-source, free, and honestly kinda fun to play with.

I'm gonna tell you about five I've tried that made me go, "Whoa, this is awesome."

What's an MCP Server?

Okay, MCP stands for Model Context Protocol. It's a way for AIs like Claude to talk to stuff outside their bubble, like websites or code notebooks. Without it, your AI's just guessing.

With it, it's like, "Hey, Claude, grab my GitHub issues," and it actually does it. I was stoked when I first got one working — it felt like I'd unlocked a cheat code.

Here are the five I've been digging into.

1. Stagehand: AI That Surfs the Web

Stagehand's this cool tool from Browserbase. It lets your AI act like it's got a browser open — clicking links, grabbing text, whatever. I used it to scrape a bunch of recipe titles from a food blog for a project, and it was way easier than writing scripts myself.

Copygit clone https://github.com/browserbase/stagehand-mcp
cd stagehand-mcp
npm install
npm start

It runs on localhost:3000. Then I told Claude (using Claude Desktop, which works great for this):

CopyGo to a news site and get the top headlines.Stagehand zipped over, snatched the titles, and Claude spit them back out. So handy for stuff like checking prices or pulling data without coding.
It's free, open-source, and doesn't break like some other web tools I've tried.

2. Jupyter: Data Stuff Without the Hassle

This one's for anyone who likes playing with numbers. The Jupyter MCP server lets your AI mess with Jupyter notebooks — you know, those coding apps for data. I'm no data scientist, but I got Claude to look at a CSV of my coffee shop spending (embarrassing, honestly) and tell me what's up.

Here's how I set it up:

Copygit clone https://github.com/jjsantos01/jupyter-notebook-mcp
cd jupyter-notebook-mcp
pip install -r requirements.txt
python server.py

It runs on localhost:8000. I told Claude:

CopyOpen coffee.csv and tell me how much I spent on lattes.

Claude made a notebook, ran some Python, and said:

CopyYou dropped $87.50 on lattes this month. Ouch.
I didn't have to write any code myself. It's like having a nerdy friend do the math for you.

3. Opik: Figuring Out What Your AI's Doing

Opik's from Comet, and it's all about keeping tabs on your AI. Like, if it starts acting weird, Opik shows you why. I had an AI bot once that kept giving dumb answers, and Opik helped me see it was hitting a limit on some API.

I got it going with:

Copygit clone https://github.com/comet-ml/opik
cd opik
./opik.sh

Then I added it to some code:

Copyimport opik

opik.configure(use_local=True)

@opik.track
def ask_something(question):
    return "You asked: " + question

ask_something("What's for dinner?")I asked Claude to check the logs:
Show me what my AI's been up to.

It showed me every call, how long it took, all that jazz.

It's like a spy for your AI, helping you catch problems fast.

4. GitHub: AI That Codes With You

This server's straight from GitHub, and it lets your AI dig into your repos. I used it when I was swamped and needed to check what was going on in a project without opening a million tabs. Claude just gave me a rundown of open issues — super helpful.

Setup's like this:

Copygit clone https://github.com/github/github-mcp-server
cd github-mcp-server
npm install
export GITHUB_TOKEN=your_token
npm start

It's on localhost:4000. I said:

CopyClaude, what's up with my repo 'side-hustle'?

Claude came back with:

CopyTwo issues open: one's a bug in the login, another's about adding a share button.
Saves me from drowning in GitHub notifications.

5. FastAPI-MCP: Your AI Calls Your APIs

FastAPI-MCP is this neat trick for turning FastAPI apps into something your AI can use. I made a little API to track my to-do list, and this let Claude check it without me doing extra work.

Here's what I did:

CopyОбъяснятьgit clone https://github.com/jlowin/fastmcp
cd fastmcp
pip install fastapi-mcpThen I tweaked my FastAPI app:
from fastapi import FastAPI
from fastmcp import mcp

app = FastAPI()

@app.get("/todo/{item_id}")
async def get_todo(item_id: int):
    return {"id": item_id, "task": f"Task {item_id}"}

@mcp.tool()
async def get_todo_tool(item_id: int):
    return await get_todo(item_id)

Ran it with uvicorn main:app — reload, hooked it to localhost:8000, and told Claude:

CopyWhat's task 5 on my to-do list?Got back:
Task 5 is "Call mom."
It's dead simple to make my own tools for Claude.

Why These Are Worth Your Time

I've had a blast with these servers. Stagehand's great for web stuff, Jupyter's awesome for data, Opik keeps things honest, GitHub's a coder's dream, and FastAPI-MCP lets me build whatever. They're all free, and you can tweak them if you're feeling fancy.

A few things I learned:

Start with one that sounds fun. I picked GitHub first 'cause I'm always in repos.
Claude Desktop's my go-to for testing this stuff.
Check GitHub for each server's readme — it's got the good stuff.
Play around locally before you go big.