Open-source cross-connector memory layer lets one agent's verified knowledge transfer to others
Neither-Witness-6010 · reddit · 2026-09-16
An indie developer is building an open-source memory layer for AI agents: persistent memory without a vector database, running as an MCP server, already working with Claude Code and Cursor. The next direction is cross-connector memory transfer — knowledge an agent learns and verifies on one platform moves to agents on other platforms as a sealed bundle with proof (command run, result, exit code) and a chain of custody, with trust decaying across unverified hops.
Concrete scenario: a PR-review agent learns the team's code conventions (verified by which PRs actually merged), transfers them to a Slack agent that answers style-rule questions with zero configuration, and a Linear triage agent stops mislabeling issues. The transfer mechanism has been tested across four platforms (Figma, Groq, ElevenLabs, Claude). The developer is now deciding whether to spend the next two months building five connector adapters or improving the core engine, and is asking production users whether per-tool memory lock-in is a real pain and whether verified-with-proof matters.
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