MCP Memory Service — Persistent Agent Memory API

Practical Notes

• Quant: the project calls out a framework-agnostic REST API with 76 endpoints—start by standardizing 5–10 “memory ops” your agents must use.
• Quant: track retrieval precision by running the same query across 10 tasks and measuring how often the top-3 hits are actually used.

How to design memory you can trust

Treat memory as data you can audit, not magical recall:

• Store short, atomic facts with tags (source, system, owner, environment).
• Always include an X-Agent-ID strategy so retrieval can be scoped.
• Separate “write” and “read” phases: write after the task, read before the task.

A simple workflow pattern

1. Task start: query with a narrow tag set.
2. During work: write only verified decisions (not raw speculation).
3. Task end: consolidate duplicates and add a short summary memory.

Safety defaults

If you enable anonymous access for local testing, keep it strictly on localhost and disable it in any shared environment.

FAQ

Q: Is this only for MCP clients? A: No. You can treat it as a plain HTTP memory service; MCP integration is optional.

Q: How do I avoid noisy memories? A: Write only verified facts and decisions, and require tags + agent scope for every write.

Q: What should I measure first? A: Retrieval precision and reuse rate: how often retrieved items are actually used in the next task.