Mem0 Mcp Server

What is Mem0 Mcp Server about?

Mem0 Mcp Server provides a persistent, searchable repository of coding preferences. It leverages Mem0 to embed and store code snippets, implementation details, and best‑practice documentation, exposing the data via an SSE endpoint that MCP clients can interact with.

How to use Mem0 Mcp Server?

1. Clone the repository and set up the environment with uv venv.
2. Activate the virtual environment: source .venv/bin/activate.
3. Install dependencies: uv pip install -e ..
4. Add your Mem0 API key to a .env file (MEM0_API_KEY=your_api_key_here).
5. Start the server: uv run main.py (default host 0.0.0.0 and port 8080).
6. In Cursor (or any MCP client), connect to http://0.0.0.0:8080/sse and use the provided tools.

Key features of Mem0 Mcp Server

• add_coding_preference – Store complete code contexts, including dependencies, versions, setup steps, documentation, examples, and best practices.
• get_all_coding_preferences – Retrieve the full set of stored preferences for review or analysis.
• search_coding_preferences – Perform semantic searches to locate relevant implementations, solutions, or documentation.
• SSE endpoint – Real‑time, low‑overhead communication for MCP clients.
• Configurable host/port – Override defaults via command‑line arguments.

Use cases of Mem0 Mcp Server

• Centralized knowledge base for a development team’s coding standards.
• Contextual assistance for AI pair‑programming agents.
• Rapid retrieval of boilerplate code and setup guides.
• Automated compliance checks against stored best‑practice patterns.

FAQ from the Mem0 Mcp Server

Q: Do I need a Mem0 account? A: Yes, an active Mem0 API key is required and should be set in the .env file.

Q: Can I change the listening port? A: Yes, start the server with uv run main.py --host <host> --port <port>.

Q: Is the server only for Cursor? A: No, any MCP‑compatible client that can connect to an SSE endpoint can use the server.

Q: How is data persisted? A: Mem0 handles storage of embeddings and metadata; the server acts as a thin request/response layer.

Q: What Python version is required? A: The project uses uv, which supports Python 3.9+.

MCP Server with Mem0 for Managing Coding Preferences

This demonstrates a structured approach for using an MCP server with mem0 to manage coding preferences efficiently. The server can be used with Cursor and provides essential tools for storing, retrieving, and searching coding preferences.

Installation

1. Clone this repository
2. Initialize the uv environment:

uv venv

3. Activate the virtual environment:

source .venv/bin/activate

4. Install the dependencies using uv:

# Install in editable mode from pyproject.toml
uv pip install -e .

5. Update .env file in the root directory with your mem0 API key:

MEM0_API_KEY=your_api_key_here

Usage

1. Start the MCP server:

uv run main.py

2. In Cursor, connect to the SSE endpoint, follow this doc for reference:

http://0.0.0.0:8080/sse

3. Open the Composer in Cursor and switch to Agent mode.

Demo with Cursor

https://github.com/user-attachments/assets/56670550-fb11-4850-9905-692d3496231c

Features

The server provides three main tools for managing code preferences:

1. add_coding_preference: Store code snippets, implementation details, and coding patterns with comprehensive context including:

   • Complete code with dependencies
   • Language/framework versions
   • Setup instructions
   • Documentation and comments
   • Example usage
   • Best practices

2. get_all_coding_preferences: Retrieve all stored coding preferences to analyze patterns, review implementations, and ensure no relevant information is missed.

3. search_coding_preferences: Semantically search through stored coding preferences to find relevant:

   • Code implementations
   • Programming solutions
   • Best practices
   • Setup guides
   • Technical documentation

Why?

This implementation allows for a persistent coding preferences system that can be accessed via MCP. The SSE-based server can run as a process that agents connect to, use, and disconnect from whenever needed. This pattern fits well with "cloud-native" use cases where the server and clients can be decoupled processes on different nodes.

Server

By default, the server runs on 0.0.0.0:8080 but is configurable with command line arguments like:

uv run main.py --host <your host> --port <your port>

The server exposes an SSE endpoint at /sse that MCP clients can connect to for accessing the coding preferences management tools.