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Cache-Pot
A superfast memory layer built for AI agents
Cache-Pot is a Redis-compatible in-memory data store, rebuilt for how AI apps and agents use a cache. Speak plain RESP2, your existing Redis client works untouched. On top: native vector search, a semantic cache (skip repeat LLM calls when a question means the same thing), a built-in MCP server so agents like Claude use it as a first-class tool, and a live web dashboard. All in one self-contained binary, no modules, no extra services.
Hey Product Hunt 👋
I built Cache-Pot because every AI project I touched ended up duct-taping the same three things onto Redis: a vector store, a semantic cache, and some bridge so an agent could actually use the cache as a tool. So I built them in.
What it is:
- **Redis-compatible core** — talks RESP2, so `redis-cli` and your existing Redis client work as-is. Point `REDIS_URL` at it and go.
- **Vector search** — `VSET` / `VSEARCH`, backed by a hybrid brute-force + HNSW index. No API key needed, you supply the vectors.
- **Semantic cache** — `SCACHE.SET` / `SCACHE.GET THRESHOLD 0.9`. Ask something close to a question you cached before, get the stored answer instead of paying for another model call.
- **Agent memory** — `REMEMBER` / `RECALL`, a simple key-value scratchpad scoped per session.
- **Native MCP server** — `cache-pot mcp` — Claude (or any MCP client) reads/writes/searches/remembers through it directly, no adapter layer.
- **Dashboard** — full web console baked into the binary: key browser, live profiler, slowlog, pub/sub, memory analysis, client list.
- **Single binary** — `go install` or Docker, nothing else to stand up.
Honest limits: no clustering/replication yet, and it's not chasing raw-throughput records against Redis/Valkey — it's built for single-node AI workloads, not to replace a Redis cluster in prod.
It's BSD-3-Clause, free, and open source, repo's linked above. Would love bug reports, "tried it with my client X" notes, and PRs, most open issues are scoped small with acceptance criteria already written, good for a first contribution.
Thanks for checking it out!
About Cache-Pot on Product Hunt
“A superfast memory layer built for AI agents”
Cache-Pot was submitted on Product Hunt and earned 8 upvotes and 3 comments, placing #159 on the daily leaderboard. Cache-Pot is a Redis-compatible in-memory data store, rebuilt for how AI apps and agents use a cache. Speak plain RESP2, your existing Redis client works untouched. On top: native vector search, a semantic cache (skip repeat LLM calls when a question means the same thing), a built-in MCP server so agents like Claude use it as a first-class tool, and a live web dashboard. All in one self-contained binary, no modules, no extra services.
On the analytics side, Cache-Pot competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Cache-Pot performed against the three products that launched closest to it on the same day.
Who hunted Cache-Pot?
Cache-Pot was hunted by Subhadip Saha. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Cache-Pot including community comment highlights and product details, visit the product overview.
Subhadip Saha