C
Limited view
67/100
2 months ago

db-memory

A vector-DB MCP server that gives Claude conversational memory by storing solved problems and solutions as vectors and retrieving relevant ones when a new request resembles a past solution.

Limited view. Automated analysis covers part of this stack. Findings reflect what we verified. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.

Limited view: static analysis for Python is partially covered.

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

Ak1Ena

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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// key findings
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
🔐
You'll be asked for 1 credential: QDRANT_API_KEY
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.
configVECTOR_BACKENDSwitchable backend — =localcloud, no code change.
configCOLLECTION_NAME
configEMBED_MODEL, delete the old Chroma memory_db/ or use a fresh Qdrant
configDB_PATH
configMIN_SCORE
configQDRANT_URL
🔐 secretQDRANT_API_KEY
configWEB_UIOptional web dashboard — flip on =on to browse the store in your browser. Off by default.
configWEB_HOST"env": { "WEB_UI": "on", "WEB_PORT": "8765", "": "127.0.0.1" }
configWEB_PORT"env": { "WEB_UI": "on", "": "8765", "WEB_HOST": "127.0.0.1" }
// 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

6/6 tools missing one or more hints — save_memory (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); search_memory (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); get_memory (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +3 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 inputs are validated

5/6 tool handlers declare input schemas (83%)

Declare an inputSchema with zod/joi/yup on every tool definition.

Tool handlers catch errors

Only 0/6 tool handlers wrap calls in try/catch (0%)

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

License file

No license file

Add a LICENSE file (MIT, Apache-2.0, etc.).

Tests exist

No test files found

Add tests that exercise each declared tool.

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 6 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/ak1ena-vector-db-mcp-4eephq)](https://m8ven.ai/mcp/ak1ena-vector-db-mcp-4eephq)
Shows your grade and updates automatically. Prefer no grade? Append ?variant=verified to the badge URL.
commit: 365aaecd045c96dfa4ca4c17eb0d59086f294519
code hash: 0be3797c29266ca2ceb8849144ab5ce021a86a83176758b54ae53f8a1f84abaa
verified: 6/18/2026, 10:30:45 AM
view raw JSON →
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