Give Claude Code, Codex and Cursor a memory of your repos
AI coding agents are powerful, but they forget how your team already solved repeated problems. Moresq Corpus turns those prior solutions into a searchable, governed memory layer for terminal agents and MCP clients.
The problem: context loss
A coding agent often regenerates authentication helpers, webhook handlers, API clients, analytics events and deployment scripts even when the repo already contains the right pattern. That wastes tokens, increases review time and creates inconsistency between projects.
Repo memory changes the workflow. The agent searches first, retrieves a short verified pattern, then writes only the project-specific adaptation. The source of truth stays in code and proof metadata, not in a long model answer.
Retrieval-first agent loop
- The terminal agent calls `search_corpus` before writing commodity code.
- Moresq Corpus returns compact matches with provenance and quality labels.
- The agent retrieves only the snippet or runbook that should be applied.
- The snippet is applied by tooling, while the model handles names, paths and glue.
- Missed searches become new snippet candidates and evaluation material.
Why this matters for AI agents
Agents get stronger when they can reuse proven local decisions. Moresq Corpus is built for that compounding effect: search hits, retrieval receipts, rejected snippets, abuse signals and apply logs all become product evidence.
The market need is direct: developers want faster agent runs without sacrificing control. Corpus gives agents memory while keeping the human review surface inspectable.