Real teams, real fleets, real memory. Case studies, integrations, and hands-on tutorials showing what governed shared memory unlocks.
A three-agent pricing fleet runs for 14 days. On Day 9 a price changes — and eight confirmed memories still assert the old value, so the synthesis agent reports it with total confidence. No error, no flag. The open-source memclaw-long-run-fleet demo fixes it with status-governed recall and an async contradiction detector that retires stale facts before the next recall.
A system prompt that says “don't surface legal data” runs after retrieval already loaded the GDPR hold into context. The open-source memclaw-cross-fleet-gov demo enforces the boundary as a SQL fleet predicate instead — three agents on one tenant, isolation that model capability can't widen, plus admin fan-out synthesis across fleets.
Five agents build a web page in sequence — a performance agent bans external scripts, an SEO agent loads a CDN library, and the page ships violating its own budget. The open-source memclaw-build-fleet reference pipeline stops it: recall before acting, write after deciding, with least privilege enforced at the MCP tool schema and again server-side via trust levels.
SpinachAI turns every meeting into clean structure. Wire it to MemClaw over MCP and that structure becomes governed memory that corrects itself — when a team reverses a decision, the old one drops out of the live answer instead of sitting there contradicting the new plan. No middleware, just two MCP servers.
NanoClaw sandboxes every agent — secure, but amnesiac. We added a shared, governed cognition layer on top: three channels (a live Telegram agent, plus Slack and Web) on one MemClaw tenant, a fact crossing channels neither other saw, and PII flagging + keystones enforced on write. The sandbox stays intact; the brain is shared.
From “hello fleet” to self-improving, governed memory — one continuous build on a single shared MemClaw stack. Multi-agent setup, the memory dashboard, scopes & keystones, the Karpathy loop, memory hygiene, and the knowledge graph. All hands-on, all open source.
A new test suite passed clean locally and failed in CI. Our error-investigation agent traced the non-obvious root cause, proved the fix under CI’s own environment, and wrote the lesson to shared memory — so next time it’s an instant recall, not another hour of bisecting.
A PR-review agent that opens every review by recalling the team’s operating rules and the design decisions behind the code — enforcing standards without re-briefing, and rejecting a change a fresh-eyes reviewer would have waved through.
Three OpenClaw agents on one self-hosted MemClaw, with fleet boundaries enforced as a storage-layer query predicate — not a prompt. The sales agent physically cannot read Legal’s compliance holds, and the admin agent surfaces the cross-fleet conflict automatically. Open-source, run it yourself.
A long-running research fleet, eight days of stale facts, and the open-source memory where the wrong answers disappear on their own — superseded automatically and suppressed by status, not by a prompt. Plus the writer ≠ verifier ≠ synthesizer pattern that keeps shared memory trustworthy.
We added a brand-new Anthropic managed agent to a real production fleet in minutes. On its first message it recalled the team’s playbook, answered like a veteran, and wrote back a rule the other agents now follow — across vendor lines, under MemClaw’s governance, owned by the client.
A community case study: Aaron wired OpenClaw and Hermes to one MemClaw instance over MCP. The dev agent wrote brand rules. The marketing agent enforced them — and caught the human's typo. The role lives in the memory, not in the agent.
Your AI tools don’t talk to each other. They can’t. MemClaw is the bestman — a shared persistent memory that holds the facts you tell Claude on Monday and hands them to ChatGPT on Thursday. The agent doesn’t live in any one product. The agent lives in the memory.
Inside the three-layer architecture a NASDAQ-listed fintech ($5.6B) built so its 300+ specialized agents share memory: 26,500+ memories, 1,372 skills, 23 ms p50 search, one governed Company Brain.
Paste one MCP config block and Cursor remembers across sessions, projects, and teammates. Personal today, governed fleet infrastructure tomorrow.
One CLI command gives Claude Code persistent memory across sessions, projects, and machines. Personal today, governed fleet infrastructure tomorrow.
Shipped something interesting on top of MemClaw? Come share it on Discord — case studies, integrations, and demos all welcome.