Agents rediscover the codebase every prompt
Dozens of exploratory file reads and greps per task, repeated for every new conversation, all billed in tokens.
For teams building with AI agents
Cursor, Claude Code, and Codex re-crawl your codebase on every prompt and infer conventions you've already standardized. That burns tokens and produces code you fix in review. Moxie Docs exposes your conventions, docs, gaps, and verified commands over the Model Context Protocol, already formatted for agents and scoped to the task.
→ get_conventions()
12 rules · paths cited
→search_docs("webhook")
top hit: billing webhook behavior
ready to write
Two scoped lookups, not 40 file reads
The problem
Dozens of exploratory file reads and greps per task, repeated for every new conversation, all billed in tokens.
Without your patterns in context, agents guess, and you catch the mismatches in review instead of shipping.
Stuffing the whole repo into the prompt is expensive, noisy, and still misses the conventions that actually matter.
The fix
Agents call get_conventions and search_docs and get exactly the context they need, replacing dozens of exploratory reads with structured, source-cited answers.
Agents follow your conventions and respect known boundaries because they're handed them up front, instead of inferring them from a partial crawl.
When an agent changes code, Moxie can propose the matching documentation update in the same pull request, so docs ship with the change, not weeks later.
FAQ
Any MCP-aware client. Claude Code, Cursor, and Codex can query Moxie's Model Context Protocol server directly for conventions, docs, gaps, and verified commands.
Yes. It's context-only and scoped per repository: conventions, docs, and citations, never billing, settings, or the merge button.
One scoped lookup replaces dozens of exploratory file reads per task, repeated across every prompt and conversation. You spend fewer tokens rediscovering the repo, and redo fewer wrong guesses in review.
Get started
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