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iai-mcp
The best open-source memory system for AI coding assistants.
The best-benchmarked open-source memory system for AI coding assistants. Your Claude or Openclaw will remember everything and you wont have to remind it what happened every session
Hi everyone, I'm Areg.
I built iai-mcp because every memory tool I tried for AI coding
assistants either forgot details I cared about or made me babysit
what was worth remembering. I wanted neither.
What it does:
- Captures every turn of every session verbatim — byte-exact, not
summarized — the moment the session ends. No "remember this"
commands.
- Consolidates during idle time into three tiers: episodic
(write-once), semantic (induced summaries from clusters),
procedural (sealed self-tuning knobs).
- Surfaces a small relevant slice of your history at the start of
each new session automatically.
- Runs as a local daemon, encrypted at rest (AES-256-GCM), zero
telemetry.
The thing I care about most: every performance claim in the README
ships with a runnable benchmark in `bench/`. Verbatim recall,
latency, RAM, token cost, contradiction handling — all of it.
Don't trust the numbers, rerun them on your machine.
I've been running this daily for months. Validated end-to-end with
Claude Code and OpenClaw. macOS only for now (Apple Silicon
tested), Linux/Windows on the way.
MIT licensed. Repo: github.com/CodeAbra/iai-mcp
Happy to answer anything — architecture choices, the three-tier
model, why the graph layer doesn't move the needle on session-shot
retrieval benchmarks (long story), or implementation gotchas.
No comment highlights available yet. Please check back later!
About iai-mcp on Product Hunt
“The best open-source memory system for AI coding assistants.”
iai-mcp was submitted on Product Hunt and earned 10 upvotes and 1 comments, placing #69 on the daily leaderboard. The best-benchmarked open-source memory system for AI coding assistants. Your Claude or Openclaw will remember everything and you wont have to remind it what happened every session
iai-mcp was featured in Productivity (651.7k followers), Open Source (68.4k followers), Artificial Intelligence (468.5k followers) and GitHub (41.2k followers) on Product Hunt. Together, these topics include over 258.3k products, making this a competitive space to launch in.
Who hunted iai-mcp?
iai-mcp was hunted by Areg Noya. 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.
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Areg Noya