Codebase intelligence layer for AI coding agents: code health, git analytics, dead code detection, and architectural decisions via MCP.
repowise is worth checking the docs before setup with strong trust signals. Check agent compatibility and use-case fit before adding it to your workflow.
gh repo view repowise-dev/repowise --webOpen the official README and confirm the supported install method.
Add the server entry to your MCP client config.
Restart your agent and verify that the server tools appear.
Repository setup guidance
Strong trust signals; still review the README and permissions before production use.
Last commit was about 96 days ago.
2203 GitHub stars indicate community interest.
25 open issues signal maintenance load.
Up-to-date code documentation for LLMs and AI code editors, eliminating outdated or hallucinated API references.
An MCP server that exposes llms.txt files to IDEs for context-aware development.
Turn OpenAPI, MCP, Doxygen, godoc, rustdoc, and Markdown into static documentation sites you own.
repowise gives your AI coding agent deep understanding of your codebase. It analyzes dependencies, git history, code health, and architecture, then exposes this intelligence through MCP tools so your agent can answer complex questions like 'why does auth work this way?' instead of just reading files. It helps reduce tool calls, file reads, and costs while improving answer quality.
repowise is an open-source codebase intelligence platform designed for AI-assisted engineering teams. It indexes your codebase into five intelligence layers: dependency graph (tree-sitter across 15 languages), git history (hotspots, ownership, co-change coupling), auto-generated documentation, architectural decisions, and code health scores. These layers are exposed via nine MCP (Model Context Protocol) tools to agents like Claude Code and Codex. Key features include: multi-repo workspace support, dead code detection, code health scoring proven to predict real bugs, and a local dashboard for visualization. repowise runs once, builds everything, then keeps in sync on every commit. It supports 15 programming languages and provides benchmarks showing reduced tool calls and costs at comparable answer quality.
Codebase intelligence layer for AI coding agents: code health, git analytics, dead code detection, and architectural decisions via MCP.
AI-assisted engineering teams using Claude Code, Codex, or other MCP-compatible agents., Tech leads and architects who need to manage technical debt and code quality across repos., DevOps and platform engineers integrating code intelligence into CI/CD pipelines.
The setup section provides repository-level starting guidance, not a guarantee of an independently verified installation. Check the official README and release notes.
repowise indexes your entire codebase locally; ensure sensitive files are excluded via configuration. MCP tools expose codebase data to AI agents; review agent permissions and data handling policies.
Similar or complementary options to evaluate include context7, mcpdoc, sourcey.
Aug 20, 2026
NOASSERTION license detected.
2 security/trust notes recorded.
Setup difficulty is 3/5.
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