LeetCode MCP — Learn MCP by Building One

This project is two things at once:

1. A gentle, from-scratch tutorial on what an MCP is and how to build one.

2. A working LeetCode MCP that connects to your LeetCode profile so an AI assistant (Cursor / Claude) can tell you whether you've solved a problem and recommend new problems by topic and difficulty.

Part 1 — What is an MCP? (the mental model)

MCP = Model Context Protocol. It's an open standard that lets an AI model safely use external tools and data. Think of it as a USB-C port for AI: any AI client that "speaks MCP" can plug into any MCP server and instantly gain new abilities.

Three roles:

An MCP server can expose three kinds of things:

• Tools — functions the AI can call (e.g. recommend_questions). ← we use this

• Resources — read-only data the AI can load (like files).

• Prompts — reusable prompt templates.

How they talk: the host launches your server as a subprocess and exchanges JSON-RPC messages over stdio (standard input/output). You don't manage that plumbing — the SDK does. You just write Python functions and decorate them.

The magic of the SDK: a function's name, docstring, and type hints are automatically turned into a schema the AI reads to know when/how to call it. That's why our functions have descriptive names and detailed docstrings.

@mcp.tool()
async def recommend_questions(topic: str, difficulty: str, count: int = 5) -> dict:
    """Recommend LeetCode problems by topic and difficulty..."""
    ...

That decorator is 90% of "creating an MCP." Everything else is normal code.

Part 2 — What THIS MCP does

It exposes three tools:

Where the data comes from

LeetCode has no official public API, but its website runs on a GraphQL endpoint at https://leetcode.com/graphql. We query it the same way the site does (see leetcode_client.py).

• Public data (problem lists, difficulty, topics) needs no login.

• Your private "solved" status requires your browser session cookies so LeetCode knows it's you. With those, every problem carries a status: "ac" = solved, "notac" = attempted, null = never tried.

Part 3 — Setup (5 minutes)

1. Install dependencies

cd /Users/akshayapratapsingh/Desktop/Leetcode-MCP
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

2. Configure your identity + cookies

cp .env.example .env

Then edit .env:

• LEETCODE_USERNAME → your username from leetcode.com/u/<username>/.

• LEETCODE_SESSION and LEETCODE_CSRF (optional but recommended) → these unlock personal "solved / not solved" detection.

How to get the cookies:

1. Log in to https://leetcode.com in Chrome.

2. Open DevTools (F12 or Cmd+Option+I).

3. Go to Application → Storage → Cookies → https://leetcode.com.

4. Copy the Value of LEETCODE_SESSION → paste into .env.

5. Copy the Value of csrftoken → paste as LEETCODE_CSRF in .env.

⚠️ These cookies are like passwords. .env is already in .gitignore so it won't be committed. Never share it. They expire every ~2 weeks; just re-copy them when your tools stop seeing your progress.

3. (Optional) quick local test without the AI

source .venv/bin/activate
python smoke_test.py        # prints your profile + a few recommendations

Part 4 — Plug it into Cursor

Cursor reads MCP servers from a JSON config. Create/edit ~/.cursor/mcp.json (global) or .cursor/mcp.json in this project, and add:

{
  "mcpServers": {
    "leetcode": {
      "command": "/Users/akshayapratapsingh/Desktop/Leetcode-MCP/.venv/bin/python",
      "args": ["/Users/akshayapratapsingh/Desktop/Leetcode-MCP/server.py"]
    }
  }
}

A ready-made copy is in .cursor/mcp.json in this repo already.

Then: Cursor Settings → MCP → you should see leetcode with a green dot and its 3 tools. Toggle it on. (For Claude Desktop, the same block goes in claude_desktop_config.json.)

Try it in chat

• "Using leetcode, have I solved Two Sum?"

• "Recommend 5 medium dynamic programming problems I haven't solved yet."

• "What's my LeetCode profile summary?"

• "Give me graph problems around difficulty medium, skip ones I've done."

Part 5 — How the code is organized

Leetcode-MCP/
├── server.py           # The MCP server: defines the 3 tools (start here)
├── leetcode_client.py  # Talks to LeetCode's GraphQL API
├── smoke_test.py       # Run the tools directly, no AI needed
├── requirements.txt    # Python dependencies
├── .env.example        # Template for your username + cookies
├── .cursor/mcp.json    # Cursor integration config
└── README.md           # This file

Reading order to learn: server.py (the tools + decorator) → leetcode_client.py (the API calls) → smoke_test.py (how to call them).

Part 6 — Ideas to extend it (great for upskilling)

• Add get_daily_challenge (LeetCode's daily problem).

• Add get_recent_submissions(username) to show your latest ACs.

• Add a Resource exposing your solved list as a browsable document.

• Cache results so you don't re-hit LeetCode on every call.

• Track a "study plan" and recommend the next problem in a curated list.

Troubleshooting