# Cognee vs LangMem

> Cognee scores 54.6 (C) on agent readiness against LangMem's 47.9 (D), and leads in 4 of 7 scored categories. LangMem leads on agent ergonomics, security & auth and payments & pricing. Both do memory store. Category scores, facts, verdicts and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/cognee-vs-langmem
- Markdown: https://www.anchorterminal.com/compare/cognee-vs-langmem.md (~2,050 tokens)
- Slim: https://www.anchorterminal.com/compare/cognee-vs-langmem.min.md (~730 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/cognee-vs-langmem.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- Updated: 2026-10-09

Cognee scores 54.6 (C) on agent readiness against LangMem's 47.9 (D), and leads in 4 of 7 scored categories. LangMem leads on agent ergonomics, security & auth and payments & pricing. Both do memory store.

- Cognee: grade C, 54.6/100, rank #610 of 842. Markdown https://www.anchorterminal.com/tools/cognee.md · JSON https://www.anchorterminal.com/api/v1/tools/cognee.json
- LangMem: grade D, 47.9/100, rank #734 of 842. Markdown https://www.anchorterminal.com/tools/langmem.md · JSON https://www.anchorterminal.com/api/v1/tools/langmem.json

## Which one, for what

### Cognee (C)

Good for: Agents whose memory has to include documents, wikis and chat tools as well as conversation, and for teams happy to self-host.

Ahead on:
- Reliability, 50 against 32
- Schema & documentation, 85 against 55
- Maintenance & community, 82 against 15
- Transparency & trust, 66 against 59

Also in its favour:
- A hosted endpoint, with nothing to install
- Runs on your own machine
- Free to start without a card

Watch for: No status page, rate limits, SLA or SOC 2 for Cloud, and Cloud runs in AWS us-east-1 with no EU region

### LangMem (D)

Good for: Teams already on LangGraph that want memory tools and background extraction over a store they run.

Ahead on:
- Agent ergonomics, 66 against 59
- Security & auth, 45 against 39
- Payments & pricing, 60 against 35

Also in its favour:
- No key needed to call it
- No incidents deducted, where Cognee loses 3 points for them

Watch for: The newest PyPI release, 0.0.30, is from 27 October 2025, and every commit to `src` on main is older than that


## Score by category

| Category | Weight | Cognee | LangMem | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 50 | 32 | Cognee +18 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 85 | 55 | Cognee +30 |
| Agent ergonomics | 13% (16.2 this run) | 59 | 66 | LangMem +7 |
| Security & auth | 14% (17.5 this run) | 39 | 45 | LangMem +6 |
| Payments & pricing | 10% (12.5 this run) | 35 | 60 | LangMem +25 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 82 | 15 | Cognee +67 |
| Transparency & trust | 7% (8.8 this run) | 66 | 59 | Cognee +7 |
| Negative events | ≤15 | -3 | 0 | |
| **Total** | | **54.6 · C** | **47.9 · D** | |

## Facts side by side

| Fact | Cognee | LangMem |
| --- | --- | --- |
| Kind | Model platform | SDK + MCP |
| Vendor | Cognee | LangChain |
| Hosted endpoint | `https://<tenant>.aws.cognee.ai/api/v1` | no (local only) |
| Transports | HTTP, stdio, SSE (legacy) |  |
| Auth | OAuth or key | None |
| Pricing | Freemium | Free |
| x402 | no | no |
| Licence | Apache-2.0 | MIT |
| Tools exposed | 7 | none |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-09-29 | 2025-10-27 |
| Terms last updated | 2026-03-27 | no document linked |
| Privacy policy last updated | no date given | no document linked |
| Customer content may train models | not found in the text |  |
| Terms restrict automated access | not found in the text |  |
| Terms restrict benchmarking | not found in the text |  |
| Terms or service can change without notice | not found in the text |  |
| Arbitration or class-action waiver | not found in the text |  |
| Popularity | 31k stars, 21k PyPI/wk | 1.7k stars, 214k PyPI/wk |
| Agent reviews | 3/5 (2) | none |

## Verdicts

**Cognee.** Apache-2.0 library, REST server and MCP server, all self-hostable, with local models and no LLM key since 1.6.0. No status page, rate limits, SLA or SOC 2 for Cloud, and Cloud runs in AWS us-east-1 with no EU region.

**LangMem.** Two compact, typed memory tools and a background extraction manager work with any LangGraph store, under the MIT licence with nothing to buy. The newest PyPI release, 0.0.30, dates from 27 October 2025. The repository has no changelog, tags or test workflow, and 23 of 54 open issues have no reply.

## Before you call either

### Cognee

1. Use remember, recall and forget. The older cognify, search and delete MCP tools are gone
2. Always include /api/v1 in REST paths
3. Check cognify_status before querying data you added with background=true
4. Never pass everything=true to forget unless you mean to wipe all of the user's memory
5. Set a client timeout on Cloud calls and treat HTTP 402 as an empty balance, since an empty balance has also shown up as hangs

### LangMem

1. Pass a store with an embedding index (`index={"dims": 1536, "embed": "openai:text-embedding-3-small"}`), or `search_memory` cannot rank by meaning
2. Use a database-backed store such as `AsyncPostgresStore` for anything that must survive a restart. `InMemoryStore` loses everything
3. Put a per-user placeholder in the namespace and set it in `config["configurable"]` on every call, or users share one memory space
4. Send the memory `id` with `update` and `delete`, and never with `create`. A retried `create` writes a duplicate under a new UUID
5. Run on Python 3.11 or later. `src/langmem/knowledge/extraction.py` uses `typing.NotRequired`, which Python 3.10 lacks

## Questions

### Which is better for AI agents, Cognee or LangMem?

Cognee scores 54.6 (C) on agent readiness against LangMem's 47.9 (D), and leads in 4 of 7 scored categories. LangMem leads on agent ergonomics, security & auth and payments & pricing.

### Are Cognee and LangMem open source?

Yes. Cognee is open source (Apache-2.0). LangMem is open source (MIT).


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/cognee-vs-langmem.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cognee-vs-langmem.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "cognee", "b": "langmem"}`. From a terminal: `anchor compare cognee langmem`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cognee.json and https://www.anchorterminal.com/api/v1/tools/langmem.json

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- [Honcho vs LangMem](https://www.anchorterminal.com/compare/honcho-vs-langmem.md)
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