# Cognee Integrations

Use when the user wants to connect cognee to external services, switching LLM or...

- Repository: https://github.com/topoteretes/cognee (32985 stars)
- Category: AI and agents
- License: Apache-2.0
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add topoteretes/cognee --skill cognee-integrations -g -a claude-code -y`
Codex: `npx skills add topoteretes/cognee --skill cognee-integrations -g -a codex -y`
Cursor: `npx skills add topoteretes/cognee --skill cognee-integrations -g -a cursor -y`
Gemini CLI: `npx skills add topoteretes/cognee --skill cognee-integrations -g -a gemini-cli -y`

## Description

Use when the user wants to connect cognee to external services, switching LLM or embedding providers (OpenAI, Azure, Gemini, Anthropic, Ollama, OpenRouter), changing databases (Postgres, PGVector, Neo4j, Neptune, Turso), S3 storage, or the MCP server for IDE integration.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Set up cognee integrations

All integration config is environment variables (`.env`). The authoritative,
always-current list with commented examples is `.env.template` at the repo
root, check it before inventing variable names. Install the matching extra
before switching a backend (e.g. `pip install cognee[postgres]`).

## LLM providers

Default is OpenAI (`LLM_API_KEY` is all you need). To switch, set
`LLM_PROVIDER`, `LLM_MODEL`, `LLM_API_KEY`, and (where relevant)
`LLM_ENDPOINT` / `LLM_API_VERSION`:

- **Azure OpenAI**: `LLM_PROVIDER=azure`, `LLM_MODEL=azure/gpt-4o-mini`, endpoint + api version required.
- **Gemini** (no extra needed): `LLM_PROVIDER=gemini`, `LLM_MODEL=gemini/gemini-2.0-flash-exp`.
- **Anthropic** (`cognee[anthropic]`): `LLM_PROVIDER=anthropic`, model e.g. `claude-3-5-sonnet-20241022`.
- **Ollama, local** (`cognee[ollama]`): `LLM_PROVIDER=ollama`, `LLM_ENDPOINT=http://localhost:11434/v1`, and set the embedding block + `HUGGINGFACE_TOKENIZER` too.
- **Custom / OpenRouter / vLLM**: `LLM_PROVIDER=custom` with the provider's OpenAI-compatible endpoint.
- **AWS Bedrock** (`cognee[aws]`): `LLM_PROVIDER=bedrock` + AWS credentials/region.

**The classic trap**: LLM and embeddings are configured independently
(`EMBEDDING_PROVIDER`, `EMBEDDING_MODEL`, `EMBEDDING_ENDPOINT`,
`EMBEDDING_API_KEY`). Configuring only one leaves the other on OpenAI, either keep a valid OpenAI key or configure both.

## Databases

The rest: https://github.com/topoteretes/cognee/blob/HEAD/.agents/skills/cognee-integrations/SKILL.md