AGPL-3.0 · Open Source · Self-hostable

Understand any codebase
in seconds.

Paste a GitHub repo URL to instantly explore its dependency graph, git intelligence, hotspots, ownership, and more.

Paste any public GitHub repo URL to instantly explore its architecture, dependencies, and more.

8
MCP tools
4
Intelligence layers
<30s
Incremental update
AGPL-3.0
License
01HOW YOU USE IT

One engine, three interfaces

Install once. Choose the interface that fits your workflow — or use all three. They share the same data, the same intelligence, the same stores.

CLI

For the solo developer

pip install repowise. Run init, update, search, dead-code, and 10 more commands. Works fully offline with Ollama. Your code never leaves your machine.

$ repowise init .
$ repowise update
$ repowise search "auth flow"
$ repowise dead-code --safe-only

MCP Server

For AI-native workflows

8 tools that plug into Claude Code, Cursor, or Cline. Your AI agent calls get_context() instead of reading 40 files. Config auto-generated after repowise init.

$ repowise mcp
$ get_overview()
$ get_context(["src/auth"])
$ get_risk(["payments.py"])

Web UI

For the whole team

Browse the wiki, explore the dependency graph in D3, view hotspot tables, track doc freshness, and chat with your codebase. All served from repowise serve.

$ repowise serve
$ localhost:7337/repos/1/wiki
$ localhost:7337/repos/1/graph
$ localhost:7337/repos/1/hotspots
03INTELLIGENCE LAYERS

Most tools answer one question.
repowise answers four.

Graph structure, git history, generated documentation, and architectural decisions — four layers that compound into genuine codebase understanding.

01
Graph Intelligence

Every dependency, ranked and traced

repowise parses your codebase into a directed dependency graph using tree-sitter ASTs across 10 languages. PageRank identifies your most critical symbols. Community detection discovers logical modules even when directory structure doesn't reflect them.

  • 6,284+ nodes with PageRank, betweenness centrality, SCC detection
  • Edge types: imports, calls, inherits, implements, co-changes
  • Topological sort drives generation order — bottom-up, always
  • Scales to 30K+ nodes with automatic SQLite-backed graph
Dependency graph visualization showing interconnected code modules ranked by PageRank
02
Git Intelligence

History that writes the documentation

GitIndexer mines your commit history to classify files as hotspots or stable, compute ownership, extract significant commit messages, and discover co-change partners. These signals flow into generation prompts, so your wiki explains why code was written — not just what it does.

  • Hotspot detection: top 25% churn + complexity files flagged
  • Co-change partners: files that change together without imports
  • Ownership from git blame — primary owner + top 3 contributors
  • Significant commits filtered and included in generation prompts
Hotspot analysis table showing file churn, complexity, risk scores, and code owners
03
Documentation Intelligence

Wiki pages that stay fresh

Each wiki page is generated with 9 layers of context: source code, symbol signatures, graph metrics, git history, import summaries, RAG context, co-change docs, dead code findings, and reverse imports. Confidence scores decay when source changes — stale pages auto-regenerate.

  • Confidence scoring: 0.0–1.0 with git-informed decay modifiers
  • RAG context via LanceDB or pgvector — each page knows its imports
  • 9-level hierarchical generation: symbols → files → modules → repo
  • Resumable jobs — crash-safe, idempotent, checkpoint after every page
Auto-generated wiki page for auth/service.py showing API signatures, ownership, and freshness score
04
Decision Intelligence

The why behind your architecture

Decisions are extracted from four sources: inline markers (# WHY:, # DECISION:, # TRADEOFF:), git archaeology, README/docs mining, and manual CLI capture. Each decision tracks staleness — when affected files change, the decision is flagged for review.

  • 4 capture sources with confidence: inline (0.95), git (0.70–0.85), docs (0.60), CLI (1.00)
  • Staleness tracking — decisions age when governed files get commits
  • Health dashboard: stale decisions, ungoverned hotspots, proposed reviews
  • MCP tool get_why() searches decisions before you change anything
Architectural decision records showing ADRs with source, confidence, and staleness tracking
09HOW WE COMPARE

The full picture, side by side

Most tools solve one slice of the problem. repowise is the only open-source platform that combines auto-generated documentation, git intelligence, decision records, and MCP tools in a single self-hostable package.

FeaturerepowiseGoogle CodeWikiDeepWikiCodeSceneSourcegraph
Self-hostable OSS
Works with private repos
Auto-generated wiki (LLM)
Git intelligence (hotspots / ownership / co-changes)
Dead code detection
Architectural decision records
MCP server for AI agents
Semantic search
Doc freshness / confidence scoring
CLAUDE.md auto-generation
Codebase chat (agentic)
Dependency graph visualization
Provider choice (4 LLM providers)
Privacy (code never leaves your infra)
repowise: 14/14 · CodeScene: 3/14 · Sourcegraph: 3/14 · DeepWiki: 4/14 · Google CodeWiki: 3/14
10GET ACCESS

Three paths to codebase intelligence

  • Self-host (free, forever)

    pip install repowise. Run on your machine, your server, your CI. AGPL-3.0. Full feature set. Your code never leaves your infrastructure.

  • Hosted (coming soon)

    Managed infrastructure, team features, shared context. Join the waitlist and we'll notify you when it's ready.

  • Enterprise

    On-prem deployment, SSO, role-based access, dedicated support, SLAs. Reach out and we'll scope it together.

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