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repowise-devCodebase intelligence for AI-assisted engineering
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<2-3 sentences summarising what the project addresses and solves, the target audience, and the benefit.> Repowise addresses the challenge of AI agents understanding complex codebases by providing "codebase intelligence." It indexes code into four layers—dependency graphs, git history, auto-generated documentation, and architectural decisions—exposing them via eight MCP-compatible tools. This enables AI assistants to grasp the context and rationale behind code, moving beyond simple text retrieval to answer "why" questions, thereby enhancing engineering productivity.
How It Works
Repowise parses codebases using tree-sitter and NetworkX to build a detailed dependency graph, analyzes git history for signals like hotspots and ownership, generates LLM-powered documentation with freshness scoring, and captures architectural decisions from history and explicit input. These four intelligence layers are made accessible through eight task-oriented MCP tools, allowing AI agents to perform complex, multi-target queries for comprehensive context retrieval.
Quick Start & Requirements
pip install repowiserepowise init (initial indexing ~25 min for 3000 files; updates <30 sec). Then, repowise serve for MCP server and local dashboard. An alternative is the Claude plugin store for automatic setup.Highlighted Details
CLAUDE.md summarizing architecture, hotspots, ownership, decisions, and dead code candidates in under 5 seconds.get_why().Maintenance & Community
The project is open-source with an active Discord community (https://discord.gg/repowise). A hosted version for teams is in active development.
Licensing & Compatibility
Licensed under AGPL v3.0, it is free for internal use. Commercial licensing for SaaS or product embedding requires contacting commercial@repowise.dev.
Limitations & Caveats
The AGPL v3 license imposes copyleft obligations. The hosted version is still under active development.
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