memotrust
Verified memory for AI agents — agents propose memories that are quarantined until verified against evidence, and recall() returns only trusted, fresh, and in-scope facts, preventing poisoned or hallucinated data from spreading.
README
<div align="center">
<img src="assets/memotrust-icon.png" alt="memotrust" width="132" />
memotrust
Your agents remember only what's true.
Verified memory for AI agents. Agents propose memories — evidence verifies them.
recall() returns only what has earned trust, so a hallucinated, stale, or
poisoned "fact" never reaches your other agents.
<br/>
<img src="assets/demo/demo.gif" alt="An agent proposes memories; a poisoned card is caught at the gate while verified memory flows to every agent." width="760" />
<br/>
npx memotrust install
</div>
The problem with agent memory
Giving agents a shared memory is a superpower — until it isn't. Every other memory layer trusts whatever the agent writes. So the moment one agent hallucinates a fact, copies a stale number, or reads a poisoned note, that mistake becomes every agent's "truth" — silently, and forever.
That's not a rough edge. It's an attack surface (memory poisoning is OWASP agentic risk ASI06) and a correctness bug (agents confidently repeat their own guesses).
memotrust flips the default
Nothing is trusted on arrival. A memory reaches
recall()only after deterministic verification against a real source, or explicit human approval. Trust decays. Disputes withhold. Every verdict keeps an auditable receipt.
- 🛡️ Poison can't spread — unverified memories are quarantined, never served. One agent's bad note can't become another agent's fact.
- ✅ Only earned trust is recalled —
recall()returns verified, fresh, in-scope memory, ranked. No guesses, no stale wins. - ⚠️ Failures come back as warnings — approaches already disproven return as warnings, so agents don't repeat a known dead end.
- 🧾 Receipts, not vibes — every verdict records the query, the reading, and the judgment. You can audit why anything is trusted.
- 📂 Just files — Markdown claims + an append-only JSONL log, git-backed. Human-readable, diffable, tamper-evident. No database.
Quick start
npx memotrust install # create the store, git-init it, register the MCP with your agent
That's it. Point Claude Code, Cursor, or any MCP client at it and your agents can
propose and recall. The dashboard rides along at http://localhost:8765.
<sub>From a checkout instead: npm install && npx tsx src/cli.ts install. Memory location resolves MEMOTRUST_HOME › a checkout's own memory/ › ~/.memotrust.</sub>
How it works
agent ──propose()──► [ proposed · quarantined ]
│
evidence ──► store judges ──► receipt (or a human approves)
│
[ trusted ]──recall()──► agents act on it
│
60-day decay / human dispute ──► withheld again
- The agent is the extractor — there is no LLM inside the store. Your agent extracts durable facts and proposes them over MCP.
- The store is the judge. To verify, the agent only ever reads a source and submits the observation; memotrust compares it to the claim's expectation, decides confirmed/refuted itself, and records the receipt. An agent cannot fake a verdict.
memotrust vs. a plain memory layer
| plain memory | memotrust | |
|---|---|---|
| New memory is… | trusted immediately | quarantined until verified |
| Hallucinated / poisoned note | served to every agent | withheld — never recalled |
| Stale facts | linger and win | decay after 60 days, re-verify |
| "We already tried that" | forgotten | returned as a warning |
| Why is this trusted? | ¯\_(ツ)_/¯ | an auditable receipt |
The tools your agent gets
| Tool | What it does |
|---|---|
recall |
Only trusted + fresh + in-scope memory, ranked; disproven approaches come back as warnings |
propose |
File a new memory — lands quarantined, never trusted on arrival |
vocabulary |
Existing spaces + tags, so agents reuse names instead of inventing synonyms |
describe_space |
One-line description when a new space first appears |
search |
Everything at any trust level, each result labeled with its status |
pending_verifications |
Claims with machine-checkable assertions awaiting a reading |
submit_evidence |
Submit a read-only observation — the store judges, not the agent |
Verification
Built-in, zero credentials — a claim opts in with a check in its frontmatter:
check: {"kind": "file", "path": "package.json", "contains": "pnpm"}
check: {"kind": "url", "url": "https://api.example.com/health", "status": 200}
check: {"kind": "command", "run": "node --version", "contains": "v22"}
command checks are disabled by default — a poisoned claim must never become
code execution from a human's verify click. Opt in with
MEMOTRUST_ALLOW_COMMAND_CHECKS=1 (runs without a shell; pipes and redirects in a
check are inert strings).
Connected sources (optional) — e.g. the Mixpanel verifier confirms growth
claims against live analytics through a read-only service account. Copy
.env.example to .env and fill in read-scoped credentials.
Dashboard
npm run serve (it also rides along whenever an agent connects). Review the inbox
(approve/reject, in bulk), watch trust coverage, audit any claim's full evidence
chain and receipts, and dispute anything that looks wrong.
Development
npm test # store + verifier unit tests
npm run test:e2e # end-to-end MCP smoke test (8 checks, real stdio, hermetic)
npm run typecheck
npm run build # compile to dist/
scripts/mcp-smoke-test.ts (npm run test:e2e) speaks real MCP over stdio against a
throwaway store and must pass against any implementation — it's the acceptance contract.
Docs
- docs/features.md — what makes it different
- docs/code-style.md — the house style the codebase holds to
License
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。