Your AI agents will become unstoppable with these five open-source MCP servers.

I've been playing around with AI lately, mostly with Claude, and I got tired of it just responding to inquiries.

You know, I wanted it to do something.
Get information from websites or look through my GitHub.

I came upon MCP servers at that point. They function as miniature helpers for your AI, enabling it to interact with tools and applications. It's free, open-source, and actually kind of fun to use.

Here are five things I've done that have left me thinking, "Whoa, this is awesome."

What is an MCP server?

Okay, MCP stands for Model Context Protocol. It enables AIs like Claude to communicate with things outside their bubble, such as webpages or code notebooks. Without it, your AI is simply guessing.

It says, "Hey, Claude, grab my GitHub issues," and it does. I was overjoyed when I first got one operating; it seemed like I'd cracked a cheat code.

Here are the five I've been looking into.

1. Stagehand: AI That Surfs the Web.

Browserbase provides a wonderful feature called Stagehand. It allows your AI to behave as if it had a browser open, visiting links and gathering text. I used it to scrape a number of recipe names from a food site for a project, and it was much easier than building my own scripts.

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

On localhost:3000, it operates. Then, using Claude Desktop, which is excellent for this, I informed Claude:

Go 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.

In contrast to some other web tools I've tried, it is open-source, free, and reliable.

2. Jupyter: Data Stuff With No Hassle

This one is for anyone who enjoys toying with numbers. The Jupyter MCP server enables your AI to interact with Jupyter notebooks, which are data coding applications. I'm not a data scientist, but I asked Claude to look at a CSV of my coffee shop expenditures (which is humiliating, to be honest) and tell me what's going on.

Here's how I configured it:

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

On localhost:8000, it operates. I said to Claude:

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

After creating a notebook and using Python, Claude stated:

You dropped $87.50 on lattes this month. Ouch.

I did not have to write any code myself. It's like asking a geeky friend to do the math for you.

3. Opik: Understanding What Your AI is Doing

Opik is from Comet, and it's all about keeping track of your AI. For example, if it begins to behave strangely, Opik will explain why. I previously had an AI bot that kept delivering nonsensical replies, and Opik helped me realize it was reaching a restriction on some API.

I got it started with:

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

After that, I included it in some code:

import 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 displayed all of the calls, wait times, and other details for me.

 It acts as your AI's spy, assisting you in quickly identifying issues.

4. AI That Codes With You: GitHub

This server, which comes directly from GitHub, enables your AI to explore your repos. When I was overloaded and needed to see what was happening on a project without opening a ton of tabs, I used it. I just received a very helpful rundown of open issues from Claude.

Configurations such as this:

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

Localhost:4000 is the address. I said:

Claude, what’s up with my repo ‘side-hustle’?

Claude returned with the following:

Two 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

This clever trick, called FastAPI-MCP, transforms FastAPI apps into AI-usable applications. Claude was able to check my to-do list without me having to do any additional work thanks to a small API I created to track it.

What I did was as follows:

git 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)

Hooked it to localhost:8000, ran it with uvicorn main:app — reload, and informed Claude:

What’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.

The Reasons These Are Time-Valuable

I've thoroughly enjoyed working with these servers. GitHub is a coder's paradise, Opik maintains integrity, Stagehand is fantastic for web content, Jupyter is fantastic for data, and FastAPI-MCP allows me to create anything. You can modify them if you're feeling fancy, and they're all free.

I found out a few things:

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.