> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cognee.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Llms integrations

# Cognee Integrations

> Integration guides for observability, orchestration frameworks, AI tooling, and partner ecosystems.

See the full overview at [https://docs.cognee.ai/llms.txt](https://docs.cognee.ai/llms.txt).

## Integrations

* [Integrations](https://docs.cognee.ai/integrations.md): Connect Cognee to agent frameworks, observability platforms, evaluation tools, and ingestion pipelines across the AI development ecosystem.
* [AWS Bedrock Integration](https://docs.cognee.ai/integrations/aws-bedrock-integration.md): Connect Cognee to AWS Bedrock models — Anthropic Claude, Amazon Titan, and others — through a LiteLLM proxy for a unified LLM interface.
* [Observability with Langfuse](https://docs.cognee.ai/integrations/langfuse-integration.md): Capture Cognee traces, generations, and custom metrics with Langfuse observability to debug and monitor AI memory pipelines in production.
* [OpenTelemetry Tracing](https://docs.cognee.ai/integrations/opentelemetry-tracing.md): Export Cognee traces as OpenTelemetry spans to OTLP backends like Tempo, Jaeger, Datadog, and Honeycomb, alongside or instead of Langfuse.
* [Observability with Keywords AI](https://docs.cognee.ai/integrations/keywordsai-integration.md): Trace Cognee tasks and workflows with Keywords AI observability through the shared @observe decorator and the cognee-community extension.
* [Built-in Evaluation Framework](https://docs.cognee.ai/integrations/eval-framework.md): Benchmark Cognee retrieval quality on multi-hop QA datasets with the built-in evaluation framework and an interactive HTML results dashboard.
* [Evaluation with DeepEval](https://docs.cognee.ai/integrations/deepeval-integration.md): Evaluate Cognee retrieval pipelines with DeepEval metrics for contextual relevancy, precision, recall, coverage, and LLM-as-a-judge scoring.
* [ScrapeGraphAI](https://docs.cognee.ai/integrations/scrapegraphai-integration.md): Scrape web pages with ScrapeGraphAI and feed extracted content straight into Cognee using prompt-based extraction and ready-made async tasks.
* [dlt (Data Load Tool)](https://docs.cognee.ai/integrations/dlt-integration.md): Ingest databases, CSV files, and dlt resources into Cognee, turning foreign keys into graph edges without LLM-based entity extraction.
* [LangGraph](https://docs.cognee.ai/integrations/langgraph-integration.md): Give LangGraph agents persistent semantic memory across sessions with Cognee — natural language recall and per-user data isolation built in.
* [Google ADK](https://docs.cognee.ai/integrations/google-adk-integration.md): Add persistent semantic memory to Google ADK agents using Cognee — structured knowledge graphs, multi-hop recall, and per-session isolation.
* [OpenClaw](https://docs.cognee.ai/integrations/openclaw-integration.md): Add persistent memory to OpenClaw agents via a Cognee plugin that auto-indexes memory files and injects relevant context before every run.
* [n8n](https://docs.cognee.ai/integrations/n8n-integration.md): Build no-code AI memory pipelines in n8n with the Cognee node — add data, cognify into a graph, and run semantic search inside workflows.
* [Claude Agent SDK](https://docs.cognee.ai/integrations/claude-agent-sdk-integration.md): Give Claude Agent SDK agents persistent cross-session memory powered by Cognee — knowledge graphs, semantic recall, and sessionized tools.
* [OpenAI Agents SDK](https://docs.cognee.ai/integrations/openai-agents-sdk-integration.md): Give OpenAI Agents SDK agents persistent structured memory with Cognee tools for graph plus vector recall and sessionized data organization.