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Add graph-backed memory and context retrieval to agent workflows

Name: Add graph-backed memory and context retrieval to agent workflows
Author: Community

Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

O que é Add graph-backed memory and context retrieval to agent workflows?

Add graph-backed memory and context retrieval to agent workflows is a Claude Code agent skill that use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

Funciona com✓Claude Code~Codex CLI~Cursor

npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/add-graph-backed-memory-and-context-retrieval-to-agent-workflows

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Documentação

O que Add graph-backed memory and context retrieval to agent workflows faz?

Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

Prerequisites

Python, Cognee, LLM provider credentials, optional graph/vector database backend

Installation

Prerequisite: Python 3.10 to 3.14.

Install Cognee with uv or pip:

uv pip install cognee
pip install cognee

For Claude Code persistent memory, upstream documents installing the Cognee integration plugin:

claude plugin marketplace add topoteretes/cognee-integrations
claude plugin install cognee-memory@cognee
Source: https://github.com/topoteretes/cognee
Extracted from upstream docs: https://raw.githubusercontent.com/topoteretes/cognee/HEAD/README.md

Documentation

https://docs.cognee.ai

Source

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