# Memori vs TencentDB Agent Memory (slim)

> TencentDB Agent Memory scores 50.9 (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/memori-vs-tencentdb-agent-memory.md (~5,850 tokens) · this version ~3,280 tokens · JSON https://www.anchorterminal.com/compare/memori-vs-tencentdb-agent-memory.json · canonical https://www.anchorterminal.com/compare/memori-vs-tencentdb-agent-memory
- 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)

TencentDB Agent Memory scores 50.9 (D) on agent readiness against Memori's 44.2 (E), and leads in 5 of 7 scored categories. Memori leads on schema & documentation and security & auth. Both do agent memory.

- Memori: E 44.2, rank #1231 of 1510 · https://www.anchorterminal.com/tools/memori.min.md
- TencentDB Agent Memory: D 50.9, rank #1049 of 1510 · https://www.anchorterminal.com/tools/tencentdb-agent-memory.min.md
- Memori, good for Memory captured from LLM calls for apps that already use OpenAI, Anthropic or Gemini clients. Ahead on Schema & documentation, 68 against 61; Security & auth, 45 against 35. Also A hosted endpoint, with nothing to install.
- TencentDB Agent Memory, good for Small teams that run several coding agents on a host they control and want shared, permissioned memory, skills and code context injected through a proxy. Ahead on Reliability, 51 against 28; Payments & pricing, 60 against 45; Maintenance & community, 70 against 33; Transparency & trust, 68 against 52. Also Free to start without a card.

| Category | Memori | TencentDB Agent Memory |
| --- | --- | --- |
| Reliability (16%) | 28 | 51 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 68 | 61 |
| Agent ergonomics (13%) | 65 | 68 |
| Security & auth (14%) | 45 | 35 |
| Payments & pricing (10%) | 45 | 60 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 33 | 70 |
| Transparency & trust (7%) | 52 | 68 |

| Fact (where they differ) | Memori | TencentDB Agent Memory |
| --- | --- | --- |
| Kind | SDK + MCP | HTTP API |
| Vendor | Memori Labs Inc. | Tencent Cloud |
| Hosted endpoint | `https://api.memorilabs.ai/mcp/` | no (local only) |
| Transports | Streamable HTTP | HTTP |
| Pricing | Freemium | Free |
| Licence | Apache-2.0 | MIT |
| Tools exposed | 7 | none |
| llms.txt | yes | no |
| Last release | 2026-05-27 | 2026-10-26 |
| Privacy policy last updated | no date given | no document linked |
| Popularity | 17k stars, 130 npm/wk, 3.8k PyPI/wk | 2.2k npm/wk |

Why the edge:
- Maintenance & community, TencentDB Agent Memory +37: 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.); TencentDB Agent Memory 70 (Release 2.0.3 on 26 October 2026 by the changelog and its tag, 9 days before this check (30). Six changelog releases in the 90 days from 6 August, 2.0.1-beta.1 (13 August), 2.0.1 (25 August), 2.0.2-beta.1 (7 September), 2.0.2 (9 October), 2.0.3-beta.1 (13 October) and 2.0.3, with image tags v1.0.2 (8 September) and v1.0.3 (22 September) between. The three stable releases 2.0.1, 2.0.2 and 2.0.3 meet the line without the pre-releases, which this run doesn't count (20). GitHub issues and pull requests weren't readable, so reply times weren't judged. The plugin changelog credits fixes to numbered issues and outside pull requests, and the README says issues get a reply within 24 hours, which we couldn't check. A workflow added on 28 October posts an automatic acknowledgement on new external pull requests, which isn't a maintainer reply (10 of 25). Official TypeScript and Python SDKs exist but only as betas, the TypeScript one last published on 14 August 2026, and the Python package name differs between the changelog and its pyproject. No MCP server, so the registry line doesn't apply (6 of 15). npm packages carry registry signatures but no provenance attestations, the deploy pulls `:latest` images, the one CI workflow skips the tests and doesn't run on the default branch, and 2.0.3 fixed a Knowledge service broken by OpenTelemetry dependency drift (4 of 10).)
- Reliability, TencentDB Agent Memory +23: 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.); TencentDB Agent Memory 51 (Local-software reading, as software the owner runs. Official multi-architecture images (amd64 and arm64) on Docker Hub's agentmemory account, named in the changelog, with Node 22.16 or later stated for the plugin and Python 3.9 or later for the SDK. Setup still needs a git clone for the start scripts, which pull `:latest` (18 of 20). Vitest suites are declared in the package files. The one CI workflow, pr-ci.yml, runs on pull requests to the main branch (the OpenClaw plugin) and installs, packs and checks the manifest, package size and skill-queue isolation without running the test suites, and nothing runs on the default branch, now feat/server_team. GitHub's Actions pages weren't readable, so no result was read (8 of 25). GitHub issues weren't readable, so open crash reports weren't counted. The changelogs list fixes for empty recall, lost memories, duplicated history and a Knowledge service that failed to start on OpenTelemetry drift, and outside pull requests (#31, #59, #79, #85) were merged into the plugin (8 of 25). Keep a Changelog with SemVer declared and upgrade notes, such as backend switches not migrating data and a v2 to v3 migration tool, but three version streams disagree (image tags 1.0.x for releases 2.0.x, the npm plugin at 1.0.3 while main's changelog stops at 0.3.6) and ROADMAP.md still says 2.0.1-beta.1 is current on 4 November (9 of 15). Release 2.0.3, but the README heads the Hub 'Team Memory Beta' and the SDKs are beta-only (8 of 15).)
- Transparency & trust, TencentDB Agent Memory +16: 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.); TencentDB Agent Memory 68 (MIT on both branches and in npm metadata, with the codegraph and Hermes Agent code it reuses credited in the README (30 of 30). The README says new chat memory and skills are private by default and sets out what each visibility means. No privacy statement says what each layer keeps or for how long. The proxy records every turn's upstream messages and model replies, the plugin's L0 and L1 retention defaults to never, `chat-memory/clear` empties L0, L1 and profile content while keeping the asset, and switching storage backends leaves data behind (12 of 30). v1 and v2 routes are marked deprecated with removal 'planned' and no date, and known limitations promise fixes 'in the next version' without dates (6 of 20). The plugin's metrics reporting is off by default and writes to local logs only, and ClickHouse analytics are off by default and documented. Core depends on OpenTelemetry exporters, and we didn't audit whether anything exports by default. The Hermes Docker image's default model endpoint is Tencent Cloud LKE, which the README states (13 of 20).)
- Payments & pricing, TencentDB Agent Memory +15: 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.); TencentDB Agent Memory 60 (Read with the self-hosted rule. MIT software with nothing to buy from Tencent, so 20 for pricing, 20 for a free start and 20 for use without an account. No x402, MPP or L402 (0). Memory extraction, wiki and code-graph building and the proxied model are paid to whichever LLM provider the owner configures.)
- Security & auth, Memori +10: Memori 45 (API keys in a header from the dashboard or CLI, with no scopes found (20 of 30). No read-only mode or per-tool restrictions (4 of 20). Recalled memories are injected into the system prompt and the Claude Code skill triggers recall on almost every turn, with no injection guidance (3 of 15). A dashboard shows memories, retrieval and usage (8 of 15). SECURITY.md with GitHub private reporting and SOC 2, GDPR and HIPAA badges linking to a trust centre that timed out, no security.txt. Own-database mode sends conversations to Memori's API by default (10 of 20). Total 45.); TencentDB Agent Memory 35 (Read as self-hosted software with a network API. Per-user `sk-mem-` keys, several per user and revocable, and OAuth2 for panel login. Against that, Memory Core's bearer gate is off by default and the .env template says setting it breaks the proxy's auth and session setup, the data plane takes team, agent and user IDs from the caller and needs only `x-tdai-service-id`, the proxy's rate-limit and session admin routes have no authentication, `/v3/instance/destroy` rests on the same unset bearer, the deploy README's defaults include an `admin` key, and the start scripts publish every port on all interfaces (8 of 30). Private-by-default assets with team, restricted and agent visibility, ACLs by user, role and agent, and read-only Knowledge tools. Data-plane deletes and `chat-memory/clear` make no user-level check and nothing asks for confirmation. Asset reads were scoped to the caller only in 2.0.2, and Agent and Task reads only in an unreleased commit of 28 October (8 of 20). The proxy injects stored memory, skills, imported documents and code into the system prompt, and we found no guidance on prompt injection or memory poisoning. Personal skills are private until shared after review (3 of 15). Participation logs, memory-generation logs and the raw L0 record let the operator trace what was written, and per-call analytics to ClickHouse is available but off by default (9 of 15). CONTRIBUTING.md asks for vulnerability reports by email to agentmemory@tencent.com rather than public issues, with no acknowledgement time, so a disclosure route without a stated time (7). No SECURITY.md on any branch, no security.txt on www.tencent.com, and no bounty or audit named. The npm plugin's postinstall runs a bash script that rewrites OpenClaw's installed files, with output sent to /dev/null. Two access-control fixes in 2026 are under the negative events.)
- Schema & documentation, Memori +7: 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.); TencentDB Agent Memory 61 (API reading for a self-hosted HTTP service. The Knowledge service has an OpenAPI 3.0.3 file of 28 paths with no security scheme. Memory Core's 109 endpoints and the proxy's routes are described only in Markdown references, and the proxy's main LLM paths are outside them (10 of 25). No website and no llms.txt. The docs are Markdown in the repository and readable raw (5 of 10). Each Core endpoint states what it does, its limits and caveats, such as which deletes skip user checks, and Knowledge's tool list marks its tools read-only. The API references and the changelog are in Chinese; the README and install guide are in English (11 of 20). Zod-checked inputs with bounds (1 to 100 messages, 8,192 characters per message, `limit` up to 100) and enums for atom types, but the reference records that `version` comes back as a string from `atomic/update` and a number from `query` (10 of 15). Worked request and response examples per endpoint and error tables per module, with the three different error-message formats set out (12 of 15). `/v3` paths with v1 and v2 routes listed as deprecated, and a dated public changelog for every release since 0.1.0 (13 of 15).)