Grapha

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Blazingly fast code intelligence that gives AI agents compiler-grade understanding of your codebase.

Grapha builds a symbol-level dependency graph from source code — not by guessing with regex, but by reading the compiler's own index. For Swift, it taps directly into Xcode's pre-built index store via binary FFI for 100% type-resolved symbols, then enriches with tree-sitter for view structure, docs, and localization. For Rust, it uses tree-sitter with Cargo workspace awareness. The result is a queryable graph with confidence-scored edges, dataflow tracing, impact analysis, and code smell detection — available as both a CLI and an MCP server for AI agent integration.

1,991 Swift files — 131K nodes — 784K edges — 8.7 seconds. Zero-copy binary FFI. Lock-free parallel extraction. No serde on the hot path.

Why Grapha

Performance

Benchmarked on a production iOS app (1,991 Swift files, ~300K lines):

Graph: 131,185 nodes · 783,793 edges · 2,983 entry points · 11,149 terminal operations

Why it's fast: zero-copy index store FFI via pointer arithmetic (no serde), lock-free rayon extraction, single shared tree-sitter parse, marker-based enrichment skip, deferred SQLite indexing, USR-scoped edge resolution. Run grapha index --timing for a per-phase breakdown.

Install

brew tap oops-rs/tap
brew install grapha

cargo install grapha

Quick Start

# Index a project (incremental by default)
grapha index .

# Search symbols
grapha symbol search "ViewModel" --kind struct --context
grapha symbol search "send" --kind function --module Room --fuzzy

# 360° context — callers, callees, reads, implements
grapha symbol context RoomPage --format tree

# Impact analysis — what breaks if this changes?
grapha symbol impact GiftPanelViewModel --depth 2 --format tree

# Complexity analysis — structural health of a type
grapha symbol complexity RoomPage

# Dataflow: entry point → terminal operations
grapha flow trace RoomPage --format tree

# Reverse: which entry points reach this symbol?
grapha flow trace sendGift --direction reverse

# Code smell detection
grapha repo smells --module Room
grapha repo smells --file Modules/Room/Sources/Room/View/RoomPage+Layout.swift
grapha repo smells --symbol RoomPageCenterContentView

# Module metrics — symbol counts, coupling ratios
grapha repo modules

# MCP server for AI agents (with auto-refresh)
grapha serve --mcp --watch

MCP Server — 11 Tools for AI Agents

grapha serve --mcp              # JSON-RPC over stdio
grapha serve --mcp --watch      # + auto-refresh on file changes

Add to .mcp.json:

{
  "mcpServers": {
    "grapha": {
      "command": "grapha",
      "args": ["serve", "--mcp", "--watch", "-p", "."]
    }
  }
}

Recall: The MCP server remembers symbol resolutions within a session. If helper is ambiguous the first time, after you disambiguate with File.swift::helper, future bare helper queries resolve automatically.

Commands

Symbols

grapha symbol search "query" [--kind K] [--module M] [--fuzzy] [--context]
grapha symbol context <symbol> [--format tree]
grapha symbol impact <symbol> [--depth N] [--format tree]
grapha symbol complexity <symbol>          # property/method/dependency counts, severity
grapha symbol file <path>                  # list declarations in a file

Dataflow

grapha flow trace <symbol> [--direction forward|reverse] [--depth N]
grapha flow graph <symbol> [--depth N]     # semantic effect graph
grapha flow entries                        # list auto-detected entry points

Repository

grapha repo smells [--module M | --file PATH | --symbol QUERY]
grapha repo modules                        # per-module metrics
grapha repo map [--module M]               # file/symbol overview
grapha repo changes [scope]                # git diff → affected symbols

Indexing & Serving

grapha index . [--full-rebuild] [--timing]
grapha analyze <path> [--compact] [--filter fn,struct]
grapha serve [--mcp] [--watch] [--port N]

Localization & Assets

grapha l10n symbol <symbol>                # resolve l10n records from SwiftUI subtree
grapha l10n usages <key> [--table T]       # find usage sites for a localization key
grapha asset list [--unused]               # image assets from xcassets catalogs
grapha asset usages <name>                 # find Image()/UIImage() references

Configuration

Optional grapha.toml at project root:

[swift]
index_store = true                         # false → tree-sitter only

[output]
default_fields = ["file", "module"]

[[external]]
name = "FrameUI"
path = "/path/to/local/frameui"            # include in cross-repo analysis

[[classifiers]]
pattern = "FirebaseFirestore.*setData"
terminal = "persistence"
direction = "write"
operation = "set"

Architecture

grapha-core/     Shared types (Node, Edge, Graph, ExtractionResult)
grapha-swift/    Swift: index store → SwiftSyntax → tree-sitter waterfall
grapha/          CLI, Rust extractor, query engines, MCP server, web UI
nodus/           Agent tooling package (skills, rules, commands)

Extraction Waterfall (Swift)

Xcode Index Store (binary FFI)      → compiler-resolved USRs, confidence 1.0
  ↓ fallback
SwiftSyntax (JSON FFI)              → accurate parse, no type resolution, confidence 0.9
  ↓ fallback
tree-sitter-swift (bundled)         → fast, limited accuracy, confidence 0.6–0.8

After index store extraction, tree-sitter enriches doc comments, SwiftUI view hierarchy, and localization metadata in a single shared parse.

Graph Model

14 node kinds: function, struct, enum, trait, protocol, extension, property, field, variant, constant, type_alias, impl, module, view, branch

10 edge kinds: calls, implements, inherits, contains, type_ref, uses, reads, writes, publishes, subscribes

Dataflow annotations: direction (read/write/pure), operation (fetch/save/publish), condition, async_boundary, provenance (source file + span)

Node roles: entry_point (SwiftUI View, @Observable, fn main, #[test]) · terminal (network, persistence, cache, event, keychain, search)

Nodus Package

nodus add wenext/grapha --adapter claude

Installs skills, rules, and slash commands (/index, /search, /impact, /complexity, /smells) for grapha-aware AI workflows.

Supported Languages

The per-language crate architecture supports adding new languages with the same waterfall pattern: compiler index → syntax parser → tree-sitter fallback.

Development

cargo build                    # Build all workspace crates
cargo test                     # Run all tests (~200)
cargo clippy && cargo fmt      # Lint + format

License

MIT