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Arbor

anandb71/arbor
122registry active
Summary

Arbor builds a semantic dependency graph of your codebase and exposes it through 10 MCP tools that answer execution-aware questions like "what breaks if I change this symbol?" Six surgical tools (get_callers, get_callees, search_symbols, get_node_detail, get_file_graph, list_entry_points) let agents traverse the graph precisely, while four broader tools handle impact analysis and pathfinding. Every response includes suggested_next_tool hints so Claude can chain queries without re-prompting. Install via `arbor bridge` for stdio transport, then run `arbor setup` in your project to build the initial graph. Works across Rust, TypeScript, Python, Go, Java, and more. Particularly useful when refactoring, reviewing blast radius before merge, or letting AI assistants understand architectural dependencies instead of treating code as flat text.

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Arbor logo

Arbor

Graph-native intelligence for codebases.
Know what breaks before you break it.

Rust CI Crates.io Latest release GHCR Glama MCP Directory MIT License

Side-by-side: an agent navigating tokio with grep-and-read (47 tool calls, still searching) vs the same agent with arbor's code graph (4 graph calls + 1 read, done)

Simulated replay — the arbor commands and their output are real (tokio @ 178k LOC). Methodology: BENCHMARKS.md

v2.5.0 — The Last Excuse · PageRank 23x faster (149.8ms → 6.6ms on a 10k-node graph). Indexing goes parallel across every core. A 178k-LOC codebase cold-indexes in 1.6s. "Indexing is slow" was the last argument for letting your agent navigate with grep -r — it's gone. Every number reproducible: BENCHMARKS.md · Release notes →


Why Arbor

Most AI coding tools treat code as text. Arbor builds a semantic dependency graph — functions, classes, and modules as nodes; calls, imports, and inheritance as edges — then answers execution-aware questions with deterministic precision:

QuestionArbor answer
If I change this symbol, what breaks?Blast radius with depth, confidence, and risk level
Who calls this — directly and transitively?Caller/callee traversal on the call graph
What's the shortest path between A and B?A* path through real dependencies
Is this PR too risky to merge?CI gate on blast-radius thresholds

No keyword guessing. No embedding hallucinations. One graph, every interface.


What's new in v2.5.0

ChangeMeasured
PageRank rewrite — flat call-graph adjacency replaces per-iteration traversal149.8ms → 6.6ms on a 10k-node graph (23x), verified side-by-side vs the old implementation
Parallel indexing — parse fans out across all cores, deterministic assemblyArbor: 253ms → 95ms · tokio (178k LOC): 2.7s → 1.6s
Warm-start centrality — watcher recomputes seed from previous scoresConverges in ~2 rounds after a one-file patch instead of the full 20-iteration budget
Convergence early-exitIteration stops at 1e-9 max delta — the budget is a ceiling, not a sentence

Zero breaking changes — cargo install arbor-graph-cli --force and everything is just faster. Think a number is wrong? cargo bench -p arbor-graph and prove it: BENCHMARKS.md.

v2.4.0 — The Agent-Native Leap (MCP 2026-07-28, HTTP transport, Tasks, MCP Apps)
FeatureWhat it does
MCP 2026-07-28Stateless server/discover, response caching (ttlMs/cacheScope), dual-version fallback for 2025-03-26 clients
Tasks extensiontasks/get · tasks/update · tasks/cancel — cold-start indexing returns task handles, not errors
MCP AppsInteractive blast-radius graph (ui://arbor/blast-radius) and architecture map (ui://arbor/architecture-map) inside agent hosts
HTTP transportarbor bridge --http --port 3333 — stateless MCP behind load balancers
Real get_blast_radiusGit-diff-aware impact analysis via shared arbor-graph::compute_blast_radius
Paginationoffset / limit / hasMore on search_symbols and get_map
BenchmarksCriterion suite + CI regression gate — see BENCHMARKS.md

Quickstart

# Install
cargo install arbor-graph-cli

# Index your project (one command)
cd your-project && arbor setup

# Explore before you edit
arbor map . --exclude-test          # ranked project skeleton (~1k tokens)
arbor refactor parse_file           # blast radius of changing a symbol
arbor diff                          # impact of uncommitted git changes

# Wire up your AI agent
claude mcp add --transport stdio --scope project arbor -- arbor bridge

Agent workflow: call get_map first → search_symbols / get_file_graph to locate code → Read only the target file. Full MCP guide →


For AI agents (MCP)

Arbor ships a production MCP server via arbor bridge. Stdio is the default; HTTP is opt-in for remote/enterprise.

# Stdio (Claude, Cursor, VS Code)
arbor bridge

# HTTP (MCP 2026-07-28)
arbor bridge --http --port 3333

Cursor / VS Code

{
  "mcpServers": {
    "arbor": {
      "type": "stdio",
      "command": "arbor",
      "args": ["bridge"]
    }
  }
}

Templates: templates/mcp/ · Setup scripts: scripts/setup-mcp.sh · scripts/setup-mcp.ps1

16 MCP tools

TierToolsUse when
Orientationget_mapFirst call — token-budgeted project skeleton ranked by PageRank
Surgicallist_entry_points · get_callers · get_callees · search_symbols · get_file_graph · get_node_detailNavigate to a specific symbol or file
Broadget_logic_path · analyze_impact · find_path · get_knowledge_pathTrace dependencies, blast radius, paths
Agent-nativeget_blast_radius · explain_symbol · audit_security · get_architecture_overview · batch_queryPR impact, onboarding, security audit, bulk lookup

Every tool returns { ok, tool, data, meta: { suggested_next_tool, suggested_next_args } } so agents chain calls without re-prompting.

Registry: io.github.Anandb71/arbor · Official API lookup · Glama listing


CLI reference

CommandDescription
arbor setupOne-shot init + index
arbor mapRanked, token-budgeted project skeleton
arbor query <term>Fuzzy symbol search (supports | OR)
arbor callers / callees <sym>One-hop graph traversal
arbor entry-pointsHTTP handlers, main, jobs, webhooks
arbor file-graph <path>Symbols + edges in one file
arbor inspect <sym>Full symbol detail
arbor path <a> <b>Shortest call-graph path
arbor refactor <sym>Blast radius before refactoring
arbor diffGit-change impact report
arbor checkCI safety gate (--max-blast-radius N)
arbor summaryAuto-generate PR description
arbor agent reviewAutonomous PR architecture review
arbor agent onboardCodebase onboarding guide
arbor agent guardReal-time architectural safety gate
arbor bridgeMCP server (add --http for HTTP transport)
arbor watchLive re-index on file changes
arbor guiNative desktop UI

All query commands support --json. map additionally supports --tokens N, --focus "pattern", --focus-changed.


Visual tour

Arbor visualizer screenshot

Full recording: media/recording-2026-01-13.mp4


Installation

# Rust / Cargo
cargo install arbor-graph-cli

# Homebrew (macOS/Linux)
brew install Anandb71/tap/arbor

# Scoop (Windows)
scoop bucket add arbor https://github.com/Anandb71/arbor && scoop install arbor

# npm wrapper (cross-platform)
npx @anandb71/arbor-cli

# Docker
docker pull ghcr.io/anandb71/arbor:latest

No-Rust installers:

  • macOS/Linux: curl -fsSL https://raw.githubusercontent.com/Anandb71/arbor/main/scripts/install.sh | bash
  • Windows: irm https://raw.githubusercontent.com/Anandb71/arbor/main/scripts/install.ps1 | iex

Pinned installs: docs/INSTALL.md


Language support

Production parsers: Rust · TypeScript / JavaScript · Python · Go · Java · C / C++ · C# · Dart

Fallback parsers: Kotlin · Swift · Ruby · PHP · Shell

Adding languages →


CI & pull requests

arbor diff --markdown
arbor check --max-blast-radius 30 --markdown
arbor summary

GitHub Action (pre-built binary, ~5s vs ~3–5min compile):

name: Arbor Check
on: [pull_request]

jobs:
  arbor:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 0

      - uses: Anandb71/arbor@v2.4.0
        with:
          command: check . --max-blast-radius 30 --markdown
          comment-on-pr: true
          github-token: ${{ secrets.GITHUB_TOKEN }}

Architecture

arbor-core (Tree-sitter parsing)
    └── arbor-graph (petgraph + PageRank + impact analysis)
            ├── arbor-cli      — CLI + MCP bridge
            ├── arbor-mcp      — MCP protocol server
            ├── arbor-server   — WebSocket JSON-RPC
            ├── arbor-watcher  — incremental file watcher
            └── arbor-gui      — desktop UI

Docs: Quickstart · Architecture · Graph schema · MCP integration · Benchmarks · Roadmap · Philosophy

Release channels: GitHub Releases · crates.io · GHCR · npm · VS Code / Open VSX · Homebrew · Scoop — Releasing guide


Philosophy

  1. Consumer first — beautiful, intuitive, instantly useful
  2. Accessibility second — works across ecosystems, runs anywhere
  3. Affordability next — minimal overhead, from laptops to monoliths

Arbor is local-first: no mandatory data exfiltration, offline-capable, open source. Security policy →


Contributing

cargo build --workspace
cargo test --workspace
cargo clippy --workspace --all-targets --all-features

CONTRIBUTING.md · Good first issues · Code of conduct


Contributors

Anandb71 holg cabinlab Karthiksenthilkumar1 zacwolfe sanjayy-j sathguru07

7 contributors | View all


License

MIT — see LICENSE.

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Registryactive
UpdatedJan 7, 2026
View on GitHub