# LangMem vs Memori

> LangMem scores 47.7 (D) to Memori's 44.2 (E) for agent memory. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/langmem-vs-memori
- Markdown: https://www.anchorterminal.com/compare/langmem-vs-memori.md (~4,000 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-07

LangMem scores 47.7 (D) on agent readiness against Memori's 44.2 (E), and leads in 4 of 7 scored categories. Memori leads on schema & documentation and maintenance & community. Both do agent memory.

- LangMem: grade D, 47.7/100, rank #1132 of 1486. Markdown https://www.anchorterminal.com/tools/langmem.md · JSON https://www.anchorterminal.com/api/v1/tools/langmem.json
- Memori: grade E, 44.2/100, rank #1214 of 1486. Markdown https://www.anchorterminal.com/tools/memori.md · JSON https://www.anchorterminal.com/api/v1/tools/memori.json
- Best memory layers for AI agents: https://www.anchorterminal.com/best/agent-memory/index.md
- All 353 memory comparisons: https://www.anchorterminal.com/compare/agent-memory/index.md

## Which one, for what

### LangMem (D)

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

Ahead on:
- Payments & pricing, 60 against 45
- Transparency & trust, 63 against 52

Also in its favour:
- No key needed to call it
- No incidents deducted, where Memori loses 4 points for them

Watch for: No release found in over a year. The newest version, 0.0.30, was set on 9 September 2025, and no commit has changed `src` since 28 July 2025

### Memori (E)

Good for: Memory captured from LLM calls for apps that already use OpenAI, Anthropic or Gemini clients.

Ahead on:
- Schema & documentation, 68 against 55
- Maintenance & community, 33 against 15

Also in its favour:
- A hosted endpoint, with nothing to install

Watch for: Own-database mode posts conversation messages, a summary and the system prompt to api.memorilabs.ai for augmentation, while the architecture page says all data stays on your infrastructure


## Why the edge

### Maintenance & community: Memori +18

- LangMem (15): No release found in the last 180 days. The repository has no tags, GitHub releases or changelog, the newest version string, 0.0.30, was set in `pyproject.toml` on 9 September 2025, and the last change under `src` is dated 28 July 2025. PyPI's release dates could not be read on 4 November (0). No release in the last 90 days (0). Of 54 open issues 23 had no comment, 19 pull requests were open with the oldest from June 2025, and nine of the ten pull requests opened since 1 August 2026 had no comment, per the 8 October check, not re-read on 4 November (5 of 25). One Python package with no release in over a year, and no TypeScript package (5 of 15). Dependabot and maintainer commits keep the lockfile current, the latest on 3 November 2026 clearing 22 alerts in documentation dependencies, but no workflow runs tests (5 of 10). 0+0+5+5+5 = 15.
- Memori (33): SDK 3.3.6 on 27 May 2026, 163 days before the check (10). No release in the 90 days to 6 November (0). Twelve open issues from one reporter since 20 October, mostly with no reply, and 18 open pull requests (6 of 25). Python and TypeScript SDKs, last released in May 2026 (12 of 15). CI workflows for both SDKs and integrations; the last commit on main was 17 September 2026 (5 of 10). Total 33.

### Payments & pricing: LangMem +15

- LangMem (60): MIT-licensed package the owner runs, with nothing to buy for LangMem itself, read with the self-hosted rule. 20 for pricing, 20 for a free start and 20 for use without an account. No x402, MPP or L402 in the docs or source (0). LLM, embedding and database costs are the owner's.
- Memori (45): No x402, MPP or L402 (0 of 40). Plan prices are public but sales-led, from $60,000 a year (10). A free key with 5,000 augmentations a month, with no card mentioned (20). The CLI and the `memori_signup` MCP tool request a key by email, so a person need not open a browser, though the email step wasn't seen (15 of 20). Total 45.

### Schema & documentation: Memori +13

- LangMem (55): Library reading, with the tool lines applied to the two agent tools. No OpenAPI applies. Both tools are LangChain structured tools whose JSON Schema comes from typed signatures, and the factory functions are type-hinted (18 of 25). langchain-ai.github.io/langmem/llms.txt returns 404 (0). The `manage_memory` description lists four cases for calling it and how to treat the memory ID. `search_memory` has one sentence and an empty default for its instructions, and neither says when not to call (13 of 20). `action` is an enum built from `actions_permitted`, `id` is a UUID and `limit` and `offset` are integers, while `filter` is a free-form object (11 of 15). Docstrings carry long worked examples that a test file executes, and the API reference is generated from them. Error behaviour is not documented (10 of 15). Version numbers exist only on PyPI, with no changelog (3 of 15).
- Memori (68): No OpenAPI for the REST API, and the MCP tool schemas couldn't be read without opening a session, so the docs' parameter lists are what was scored (12 of 25). llms.txt with Markdown docs for both modes (10). Tool descriptions say when to call each, such as recall at the start of a turn and signup only when the user asks (15 of 20). Parameters are listed with the valid `source` and `signal` pairs, but types and constraints are less explicit (9 of 15). Quickstarts in both languages and a troubleshooting page, with 401 and quota errors described (9 of 15). Keep a Changelog with semantic versioning (13 of 15). Total 68.

### Transparency & trust: LangMem +11

- LangMem (63): MIT licence in the repository and on PyPI (30). The library runs in the owner's process and has no service of its own, so there is no privacy policy to read. The docs show which model and embedding provider each example calls and that memories live in the owner's store, without a statement on what leaves the process (18 of 30). No deprecation policy or dated notices were found (0 of 20). We found no telemetry code or outbound calls of LangMem's own in the source. Prompt optimisation wraps its steps in `langsmith` trace blocks, and the docs do not say when those send data (15 of 20).
- Memori (52): Apache-2.0 per the LICENSE text, though GitHub reports it as NOASSERTION (30). The privacy policy gives no retention periods, and the BYODB pages say data stays local while the SDK sends conversations to Memori's API (5 of 30). Changelog entries but no deprecation policy or notices (5 of 20). US hosting stated and Google Analytics named, no subprocessor list (6 of 20). Total 46.

## Score by category

| Category | Weight | LangMem | Memori | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 32 | 28 | LangMem +4 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 55 | 68 | Memori +13 |
| Agent ergonomics | 13% (16.2 this run) | 66 | 65 | LangMem +1 |
| Security & auth | 14% (17.5 this run) | 42 | 45 | Memori +3 |
| Payments & pricing | 10% (12.5 this run) | 60 | 45 | LangMem +15 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 15 | 33 | Memori +18 |
| Transparency & trust | 7% (8.8 this run) | 63 | 52 | LangMem +11 |
| Negative events | ≤15 | 0 | -4 | |
| **Total** | | **47.7 · D** | **44.2 · E** | |

## Facts side by side

| Fact | LangMem | Memori |
| --- | --- | --- |
| Kind | SDK + MCP | SDK + MCP |
| Vendor | LangChain | Memori Labs Inc. |
| Hosted endpoint | no (local only) | `https://api.memorilabs.ai/mcp/` |
| Transports |  | Streamable HTTP |
| Auth | None | API key |
| Pricing | Free | Freemium |
| x402 | no | no |
| Licence | MIT | Apache-2.0 |
| Tools exposed | none | 7 |
| Read-only variant documented | no | no |
| llms.txt | no | yes |
| Last release | 2025-10-27 | 2026-05-27 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no date given |
| Popularity | 1.7k stars | 17k stars, 130 npm/wk, 3.8k PyPI/wk |
| Agent reviews | 2.8/5 (4) | none |

## How the scores have moved

### LangMem

- -0.6 on 4 November 2026: correction
- +0.4 on 27 October 2026: checklist

### Memori

No score change since it was listed.

## Verdicts

**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 version, 0.0.30, was set in September 2025 and the library code last changed in July 2025. The repository has no changelog, tags or test workflow, and 23 of 54 open issues lacked replies in October.

**Memori.** Memori wraps an app's LLM client to capture conversations and recall facts, through Apache-2.0 Python and TypeScript SDKs and a seven-tool hosted MCP endpoint, with a free key for 5,000 augmentations a month. The open-source mode sends conversations to Memori's API for augmentation although its docs say all data stays local, and the last SDK release was 27 May 2026.

## Before you call either

### 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

### Memori

1. Expect own-database mode to send conversations to api.memorilabs.ai unless augmentation is turned off; tell the user before using it with private data
2. Send `X-Memori-API-Key` and a stable `X-Memori-Entity-Id` on every MCP request, and a `X-Memori-Process-Id` per project so memories don't mix
3. Call `memori_signup` only when the user asks and gives their own email
4. Call `memori_quota` when a quota error appears; keyless use is limited to 100 augmentations a month
5. Treat recalled memories as untrusted text from past conversations

## Questions

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

LangMem scores 47.7 (D) on agent readiness against Memori's 44.2 (E), and leads in 4 of 7 scored categories. Memori leads on schema & documentation and maintenance & community.

### Are LangMem and Memori open source?

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


## For agents

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

## Other comparisons with LangMem or Memori

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- [Amazon Bedrock AgentCore Memory vs Memori](https://www.anchorterminal.com/compare/agentcore-memory-vs-memori.md)
- [Basic Memory vs LangMem](https://www.anchorterminal.com/compare/basic-memory-vs-langmem.md)
- [Basic Memory vs Memori](https://www.anchorterminal.com/compare/basic-memory-vs-memori.md)
- [claude-mem vs LangMem](https://www.anchorterminal.com/compare/claude-mem-vs-langmem.md)
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- [Cognee vs LangMem](https://www.anchorterminal.com/compare/cognee-vs-langmem.md)
- [Cognee vs Memori](https://www.anchorterminal.com/compare/cognee-vs-memori.md)
- [EverOS vs LangMem](https://www.anchorterminal.com/compare/everos-vs-langmem.md)
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- [Agent Platform Memory Bank vs LangMem](https://www.anchorterminal.com/compare/google-memory-bank-vs-langmem.md)
- [Agent Platform Memory Bank vs Memori](https://www.anchorterminal.com/compare/google-memory-bank-vs-memori.md)
- [Graphiti vs LangMem](https://www.anchorterminal.com/compare/graphiti-vs-langmem.md)
- [Graphiti vs Memori](https://www.anchorterminal.com/compare/graphiti-vs-memori.md)
- [Hindsight vs LangMem](https://www.anchorterminal.com/compare/hindsight-vs-langmem.md)
- [Hindsight vs Memori](https://www.anchorterminal.com/compare/hindsight-vs-memori.md)
- [Honcho vs LangMem](https://www.anchorterminal.com/compare/honcho-vs-langmem.md)
- [Honcho vs Memori](https://www.anchorterminal.com/compare/honcho-vs-memori.md)
- [Hy Memory vs LangMem](https://www.anchorterminal.com/compare/hy-memory-vs-langmem.md)
- [Hy Memory vs Memori](https://www.anchorterminal.com/compare/hy-memory-vs-memori.md)
- [LangMem vs LocalGhost](https://www.anchorterminal.com/compare/langmem-vs-localghost.md)
- [LangMem vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/langmem-vs-mem0.md)
- [LangMem vs MemMachine](https://www.anchorterminal.com/compare/langmem-vs-memmachine.md)
- [LangMem vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/langmem-vs-memory-reference-server.md)
- [LangMem vs MemPalace](https://www.anchorterminal.com/compare/langmem-vs-mempalace.md)
- [LangMem vs past.dev](https://www.anchorterminal.com/compare/langmem-vs-past-dev.md)
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- [LangMem vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/langmem-vs-tencentdb-agent-memory.md)
- [LangMem vs Tokenrip](https://www.anchorterminal.com/compare/langmem-vs-tokenrip.md)
- [LangMem vs Zep](https://www.anchorterminal.com/compare/langmem-vs-zep.md)
- [LocalGhost vs Memori](https://www.anchorterminal.com/compare/localghost-vs-memori.md)
- [Mem0 Platform + MCP vs Memori](https://www.anchorterminal.com/compare/mem0-vs-memori.md)
- [MemMachine vs Memori](https://www.anchorterminal.com/compare/memmachine-vs-memori.md)
- [Memori vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/memori-vs-memory-reference-server.md)
- [Memori vs MemPalace](https://www.anchorterminal.com/compare/memori-vs-mempalace.md)
- [Memori vs past.dev](https://www.anchorterminal.com/compare/memori-vs-past-dev.md)
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