# LangMem vs Memori (slim)

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

- Full: https://www.anchorterminal.com/compare/langmem-vs-memori.md (~4,000 tokens) · this version ~1,730 tokens · JSON https://www.anchorterminal.com/compare/langmem-vs-memori.json · canonical https://www.anchorterminal.com/compare/langmem-vs-memori
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-07
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

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: D 47.7, rank #1132 of 1486 · https://www.anchorterminal.com/tools/langmem.min.md
- Memori: E 44.2, rank #1214 of 1486 · https://www.anchorterminal.com/tools/memori.min.md
- LangMem, 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 No key needed to call it; No incidents deducted, where Memori loses 4 points for them.
- Memori, 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 A hosted endpoint, with nothing to install.

| Category | LangMem | Memori |
| --- | --- | --- |
| Reliability (16%) | 32 | 28 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 55 | 68 |
| Agent ergonomics (13%) | 66 | 65 |
| Security & auth (14%) | 42 | 45 |
| Payments & pricing (10%) | 60 | 45 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 15 | 33 |
| Transparency & trust (7%) | 63 | 52 |

| Fact (where they differ) | LangMem | Memori |
| --- | --- | --- |
| 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 |
| Licence | MIT | Apache-2.0 |
| Tools exposed | none | 7 |
| llms.txt | no | yes |
| Last release | 2025-10-27 | 2026-05-27 |
| 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 |

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.)