Reliable LLM Memory for AI Applications and AI Agents
cognee MCP server
Installing Manually
A MCP server project
-
Clone the cognee repo
-
Install dependencies
brew install uv
cd cognee-mcp
uv sync --dev --all-extras --reinstall
- Activate the venv with
source .venv/bin/activate
- Add the new server to your Claude config:
The file should be located here: ~/Library/Application\ Support/Claude/
cd ~/Library/Application\ Support/Claude/
You need to create claude_desktop_config.json in this folder if it doesn’t exist Make sure to add your paths and LLM API key to the file bellow Use your editor of choice, for example Nano:
nano claude_desktop_config.json
{
"mcpServers": {
"cognee": {
"command": "/Users/{user}/cognee/.venv/bin/uv",
"args": [
"--directory",
"/Users/{user}/cognee/cognee-mcp",
"run",
"cognee"
],
"env": {
"ENV": "local",
"TOKENIZERS_PARALLELISM": "false",
"LLM_API_KEY": "sk-"
}
}
}
}
Restart your Claude desktop.
Installing via Smithery
To install Cognee for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install cognee --client claude
Define cognify tool in server.py Restart your Claude desktop.
To use debugger, run:
mcp dev src/server.py
Open inspector with timeout passed:
http://localhost:5173?timeout=120000
To apply new changes while developing cognee you need to do:
poetry lock
in cognee folderuv sync --dev --all-extras --reinstall
mcp dev src/server.py
Prerequisites
- •Familiarity with the server domain
- •Basic understanding of related technologies
- •Knowledge of Data & Storage
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