Back to MCP Trust Indexm8ven
C
Emerging
74/100
2 months ago

loom

Provides persistent identity and memory for AI agents across MCP-compatible harnesses, enabling agents to retain their name, values, and episodic memories between sessions regardless of the client or model.

→ sleepunit-agents/loom· listed on glama

Emerging. No concerning findings. Grades remain capped until the project builds reputation through adoption. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.

How we verified

Code Verified⚡ Live Monitored: not connected

Verified is a snapshot. Live keeps it current, and builds your track record.

⚡ Connect GitHub → continuous verification on every pushwhy connect →

Who stands behind it

sleepunit-agents

Source: Glama

Is this your MCP?

Claim it to get a verified publisher badge, a free copy of our full audit findings, and direct contact for any high-priority issues we find. Or connect your repo for our deepest verification, Live Monitored: read-only, revoke anytime. What we access →

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Install from

Glama

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// key findings
✅
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
✅
Open source with a license and README
Anyone can audit the code, the license is declared, and the publisher documents what it does.
🔐
You'll be asked for 1 credential: LOOM_BEARER_TOKEN
These are read from process.env at runtime. Make sure you trust where they’ll be sent.
// environment variables
To run this server yourself, you supply these values. They go in your own MCP client configuration and stay on your machine. The secret label means the value is sensitive, not that the server mishandles it.
🔐 secretLOOM_BEARER_TOKEN
configLOOM_CLIENT, LOOM_MODEL) are honored.
configLOOM_CONTEXT_DIRper-command usage. All global env vars (,
configLOOM_FASTEMBED_CACHE_DIR~/.cache/loom/fastembed/ Where to cache ONNX models
configLOOM_FASTEMBED_MODELfast-bge-small-en-v1.5 fastembed model ID
configLOOM_HTTP_HOST
configLOOM_HTTP_PORT
configLOOM_KNOWLEDGE_DB_PATH
configLOOM_MODELLOOM_CLIENT, ) are honored.
configLOOM_QDRANT_COLLECTION
configLOOM_QDRANT_URL
configLOOM_SQLITE_DB_PATHcontext>/memories.db Override the memory DB path
// quality suggestions

Tool annotations

No tools have read-only/destructive annotations

Add readOnlyHint or destructiveHint annotations to every tool so hosts can warn users before invoking.

All four hints declared on every tool

26/26 tools missing one or more hints — identity (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); dossier (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); remember (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +23 more. OpenAI's directory rejects tools where any of the four hints are missing or non-boolean.

For every tool, set all four hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) to explicit true/false values that match the handler’s actual behaviour.

Tool handlers catch errors

Only 0/26 tool handlers wrap calls in try/catch (0%)

Wrap each tool handler body in try/catch and return a structured error response.

Tool test coverage

Only 6/26 tools referenced in tests (23%)

Write tests that reference each tool by name so every tool has at least one test.

Shell command execution

4 child_process calls — runs shell commands

Prefer library functions over shell-outs. If you must shell out, ensure all inputs are properly escaped.

Claim the listing to review these findings one by one and send us a correction where you disagree, straight to the team. Claiming also means we tell you when the grade moves, and reach you first if we find anything urgent.

// full audit trail
The findings above are the summary. The full trail, every check we ran, each deduction, the network hosts observed and the dependency advisories, goes to verified publishers, along with an alert whenever a new one lands. Verified publishers can also review each finding and dispute it in one click. Publisher corrections have sharpened several of our checks this month, because the maintainer knows the codebase better than any scanner.
// improvement guidance — verified publishers only
We have 5 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
// embed badge in your README
[![M8ven Score](https://m8ven.ai/badge/mcp/jbarket-loom-1kcyi9)](https://m8ven.ai/mcp/jbarket-loom-1kcyi9)
Shows your grade and updates automatically. Prefer no grade? Append ?variant=verified to the badge URL.
commit: 9633f6dfc4bb23505b865454551ba6dc79a28b95
code hash: a48d469902ae44e273f3268f68f0f72a028380d8feb3a949cae0e4f1d1005d7b
verified: 6/15/2026, 2:20:32 PM
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