Graphicle vs Cognee: memory for coding agents.
Cognee turns documents, data and code into a knowledge graph for AI agents. Graphicle remembers a repository's docs, decisions and past agent sessions, beside a code graph, for coding agents.
Checked against Cognee's own pages on 27 October 2026
Cognee and Graphicle.
Cognee is an open-source memory engine that turns documents, data and code into a knowledge graph for AI agents, locally and with no API key, over MCP and a Claude Code plugin.
| Cognee | Graphicle | |
|---|---|---|
| Built for | AI agents and apps | Coding agents in a repository |
| Code | A graph of symbols and dependencies | A Rust port of Graphify's engine |
| Model needed | A local model, or an LLM you set | Only to propose memories; local models work |
| New memories | Built from your data | Wait for your approval; sources kept word for word |
| Licence | Apache-2.0 | Apache-2.0 |
What we measured.
- 87.66 vs 69.48LoCoMo-10, against Cognee 1.6.3Graphicle ahead
- 12 vs 206estimated model calls per conversation while ingesting LoCoMo-10
A pre-release comparison with seven memory systems: development sets; one open model as every system's reader, judge and model; a pre-release build of Graphicle, not its released defaults. These scores cannot be set against any vendor's published numbers, and the call counts per conversation are estimates. On LME-84 and BEAM-100K Graphicle led on the primary measure but did not meet every condition of the registered rule, so neither counts as ahead.
Which one fits.
Choose Cognee if
- You want knowledge-graph memory over many kinds of data, in your own pipelines.
Choose Graphicle if
- Your memory is for coding agents, next to the code graph.
- You want memories to wait for your approval.
Checked on 27 October 2026. Product names are trademarks of their owners; no affiliation or endorsement is implied.