# MemMachine vs Memori (slim)

> MemMachine scores 58 (C) 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/memmachine-vs-memori.md (~4,100 tokens) · this version ~1,880 tokens · JSON https://www.anchorterminal.com/compare/memmachine-vs-memori.json · canonical https://www.anchorterminal.com/compare/memmachine-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)

MemMachine scores 58 (C) on agent readiness against Memori's 44.2 (E), and leads in 4 of 7 scored categories. Memori leads on payments & pricing. Both do agent memory.

- MemMachine: C 58, rank #771 of 1510 · https://www.anchorterminal.com/tools/memmachine.min.md
- Memori: E 44.2, rank #1231 of 1510 · https://www.anchorterminal.com/tools/memori.min.md
- MemMachine, good for Self-hosted memory for agent frameworks that want episodic and profile memory with many integrations. Ahead on Reliability, 51 against 28; Schema & documentation, 79 against 68; Maintenance & community, 83 against 33; Transparency & trust, 57 against 52. Also No key needed to call it; Runs on your own machine; 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 Payments & pricing, 45 against 40. Also A hosted endpoint, with nothing to install.

| Category | MemMachine | Memori |
| --- | --- | --- |
| Reliability (16%) | 51 | 28 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 79 | 68 |
| Agent ergonomics (13%) | 65 | 65 |
| Security & auth (14%) | 41 | 45 |
| Payments & pricing (10%) | 40 | 45 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 83 | 33 |
| Transparency & trust (7%) | 57 | 52 |

| Fact (where they differ) | MemMachine | Memori |
| --- | --- | --- |
| Kind | HTTP API | SDK + MCP |
| Vendor | MemVerge, Inc. | Memori Labs Inc. |
| Hosted endpoint | no (local only) | `https://api.memorilabs.ai/mcp/` |
| Transports | HTTP, stdio, Streamable HTTP | Streamable HTTP |
| Auth | None | API key |
| Tools exposed | 3 | 7 |
| Last release | 2026-10-08 | 2026-05-27 |
| Terms last updated | no date given | no document linked |
| Privacy policy last updated | 2026-05-20 | no date given |
| Customer content may train models | not found in the text | not read yet |
| Terms restrict automated access | yes | not read yet |
| Terms restrict benchmarking | yes | not read yet |
| Terms or service can change without notice | not found in the text | not read yet |
| Arbitration or class-action waiver | yes | not read yet |
| Popularity | 3.1k stars, 28 npm/wk, 581 PyPI/wk | 17k stars, 130 npm/wk, 3.8k PyPI/wk |

Why the edge:
- Maintenance & community, MemMachine +50: MemMachine 83 (v0.4.0 on PyPI on 8 October 2026, 29 days before the check (30). v0.3.9-post1, v0.4.0, v0.4.1-dev0 and v0.4.1-a1 in 90 days (20). Many open issues and recent reports with few replies (12 of 25). Python and TypeScript clients, both current (12 of 15). uv lock checks, security audit, SBOM and stale-issue workflows (9 of 10). Total 83.); 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.)
- Reliability, MemMachine +23: MemMachine 51 (Local-software lines, as a server the owner runs. `memmachine-server` and `memmachine-client` on PyPI with Python versions stated, a Docker image and a compose script (20). pytest, integration and installation-test workflows exist, but GitHub's API answered with a rate limit, so run results were unread (15 of 25, unchecked). 292 open issues and pull requests; the newest bug reports, including a 429 from a provider surfacing as a 500 and a 0.4.0 configuration that no longer starts, have zero to two replies (10 of 25). No changelog file, release notes only on GitHub, which weren't read, and pre-1.0 tags (6 of 15). Version 0.4.0 (0). Total 51.); Memori 28 (Hosted lines, since both modes call Memori's API. No status page found; status.memorilabs.ai did not answer and none is linked (0). No readable incident history (5). Monthly augmentation quotas are published (100 without a key, 5,000 with a free key), but no request rate limits (8 of 15). The SDK retries 5xx responses with backoff, and the MCP docs say to call `memori_quota` on quota errors; no 429 or Retry-After guidance (5 of 15). SLA only as a custom Enterprise term (0). No beta label on the cloud or MCP endpoint (10). Total 28.)
- Schema & documentation, MemMachine +11: MemMachine 79 (OpenAPI documents for the server (54 operations) and the hosted platform (12) (25). llms.txt on docs.memmachine.ai with Markdown pages (10). Every operation has a description, and the docs explain memory types and scoping (15 of 20). Typed request models generated from the server, with search options for limits and filters (12 of 15). Examples for each client and the MCP tools, but only 422 is documented on the server and the README's first example doesn't run (8 of 15). `/api/v2` paths and tagged releases, no changelog (9 of 15). Total 79.); 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.)
- Payments & pricing, Memori +5: MemMachine 40 (Self-hosted rule, with the price lines read for the hosted platform. No x402, MPP or L402 (0 of 40). No hosted prices found on the site or docs (0). Free to self-host with no card (20). An agent can install it from PyPI with no account (20). Total 40.); 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.)
- Transparency & trust, MemMachine +5: MemMachine 57 (Apache-2.0 (30). The terms say hosted customer data is destroyed on termination, with no period, and use usage data only in aggregate; the privacy policy wasn't read (12 of 30). No deprecation policy or notices found (3 of 20). No telemetry calls found in the server or client source, and the docs don't address it (10 of 20). Total 55.); 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.)