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Grounded in available product and source data
Long-term memory for AI-coded codebases.
AI writes the code; the reason it chose that approach lives in a chat
window that's gone by morning. Selvedge is a
git blame for the why — a local MCP server your agent
(Claude Code, Cursor, Copilot) calls as it works, recording the intent behind
each change in the moment it makes it, not reconstructing it from the diff
afterward.
Six months ago, your AI agent added a column called user_tier_v2. You don’t know why.
git blame points to a commit from claude-code with a generated message that says
“Update schema.” The session that made the change is long gone — and so is the prompt
that produced it.
That reasoning was captured by the agent in the moment — written into Selvedge from
the same context that produced the change. Not inferred from the diff afterward by a
second LLM. Not a hand-typed commit message.
It also reads back out: Selvedge exports its history as Agent Trace
records, so the why travels into whatever observability or audit tooling already speaks
that format.
AI agents call Selvedge’s MCP tools while they work — log_change records what they
changed and why, in the same context window that produced the change.
Every change is tagged to the thing you actually search for — users.email,
env/STRIPE_SECRET_KEY, api/v1/checkout, deps/stripe — not a line number.
Search users and you get everything under it.
Almost nothing to install, nothing to run. A SQLite file under .selvedge/
next to your code. No accounts, no servers, no telemetry.
