58
grade D
2 days ago
glama
Prompt Learning MCP Server
Provides stateful prompt optimization using research-backed techniques like APE and OPRO, learning from historical performance data via a vector database. It enables users to automatically refine prompts, retrieve high-performing examples, and track performance analytics through iterative feedback.
Install from
M8ven verifies MCPs across every public registry — install directly from whichever one you prefer.
// key findings
🚨
Known vulnerabilities in dependencies: 1 critical, 2 high
Affects packages this MCP installs at runtime. Upgrade or remove the affected dependency.
⚠️
Tests do not pass
Either the test suite is broken or the code regressed. Either way the published behaviour can’t be verified by the publisher’s own tests.
🔐
You'll be asked for 1 credential: OPENAI_API_KEY
These are read from process.env at runtime. Make sure you trust where they’ll be sent.
// required environment variables
This server reads these from
process.env. You'll be asked to provide them before it can run.🔐 secret
OPENAI_API_KEY— "": "sk-..."config
REDIS_URL— "": "redis://localhost:6379",config
VECTOR_DB_URL— "": "http://localhost:6333",// full audit trail
The full breakdown of what we checked, the deductions that landed, the network hosts, the dependency advisories, and concrete fix guidance is available to verified publishers.
// improvement guidance — verified publishers only
We have 7 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
[](https://m8ven.ai/mcp/curiositech-prompt-learning-mcp-1fvias)commit: 8768b46fcfe36208e75e6068c9efc325c2f65d18
code hash: 2e1e7e312febcc4a147cf2a43adc10341d9b3ec1c9ed2f933423f263e0bd489d
verified: 4/18/2026, 6:23:44 PM