Memory (calvin-francis/memory-mcp) is an MCP server listed on the M8ven Trust Index. It scores 74 out of 100, grade C. It declares 14 tools. No publisher has claimed this listing.

Back to MCP Trust IndexM8ven
C
Emerging
74/100

Memory

Persistent conversational memory with semantic search using PostgreSQL and pgvector, combining traditional memory storage with confidence scoring and a bidirectional knowledge graph for entity relationships

→ calvin-francis/memory-mcp· listed on pulsemcp

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

⚡ Live Monitored: not connected

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Who stands behind it

calvin-francis

Source: PulseMCP · also listed on Glama

Is this your MCP?

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Install from

PulseMCPnot scored hereGlamanot scored here

The grade above is for the source repository. Registries can serve a different version, so we mark the ones we were not able to read.

⏳ This MCP is queued for scoring. Check back in a few minutes.
// 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: DASHSCOPE_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.
🔐 secretDASHSCOPE_API_KEY"": "sk-your-api-key"
configDASHSCOPE_API_URL❌ https://dashscope.aliyuncs.com/... 嵌入 API 端点
configDB_IDLE_TIMEOUT❌ 30000 空闲连接超时 (ms)
configDB_MAX_POOL_SIZE❌ 20 数据库连接池大小
configEMBEDDINGS_DIMENSIONS❌ 1024 向量维度
configEMBEDDINGS_MODEL❌ text-embedding-v3 嵌入模型
configMCP_DEBUG_LOG_PATH❌ memory-debug.log 调试日志路径
configMCP_PROTOCOL_VERSION
configMCP_SERVER_DESCRIPTION
configMCP_SERVER_DISPLAY_NAME
configMCP_SERVER_NAME
configMCP_SERVER_PUBLISHER
configMCP_SERVER_VERSION
configSEARCH_DEFAULT_LIMIT❌ 10 默认搜索结果数
Deployment configuration, supplied by whoever hosts the server. Users are not asked for these.
deployDATABASE_URL
deployPORT
// 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

14/14 tools missing one or more hints — memory_create (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); memory_search (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); memory_list (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +11 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.

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 3 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/calvin-francis/memory-mcp)](https://m8ven.ai/mcp/calvin-francis/memory-mcp)
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commit: 6586b3a8d4f9c64ef69c812ddf5e7c00ebd18be6
code hash: b3dd8df3e0e58541c8e761f201944a8aaa2732e55b5e987d89c9a86974b16874
view raw JSON →
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