Which integrations are available for this server?

Provides Git-aware analysis for Go projects, supporting incremental updates to the call graph and integration with Git hooks to keep the analysis synchronized with code changes. Enables the export of call graph analysis, impact assessments, and function relationship data into Markdown format for use as context in RAG (Retrieval-Augmented Generation) workflows.

crag - Call Graph for AI-Assisted Go Development

Go Version License

AI modifies a function but misses 5 callers that also need updating. crag fixes this — it builds precise call graphs via static analysis, so AI knows exactly what's affected before making changes.

How It Works

crag analyze .          # Build call graph using SSA + VTA static analysis
                        # → Stored in SQLite, fast to query

AI: "Modify ProcessRequest"
 → crag automatically finds all 5 callers
 → AI updates them together, nothing missed

Install

go install github.com/zheng/crag/cmd/crag@latest

Quick Start

# 1. Analyze your Go project
crag analyze . -o .crag.db

# 2. Configure MCP for your AI editor (Cursor / Claude Code)
# Add to .cursor/mcp.json or claude_desktop_config.json:

{
  "mcpServers": {
    "crag": {
      "command": "crag",
      "args": ["mcp", "-d", "/absolute/path/.crag.db"]
    }
  }
}

# 3. Keep it updated (pick one)
crag watch . -d .crag.db          # Auto-update on file changes
# or: add `crag analyze . -i` to .git/hooks/post-commit

That's it. Your AI editor can now query call graphs directly.

What AI Can Do With crag

After MCP setup, just ask naturally:

"Where is HandleRequest called?" → upstream callers
"If I change BuildSSA, what's affected?" → impact analysis
"Find all functions containing Auth" → search

CLI Usage

crag impact "HandleRequest" -d .crag.db    # Impact analysis (callers + callees)
crag upstream "db.Query" -d .crag.db       # Who calls this? (recursive)
crag downstream "Process" -d .crag.db      # What does this call?
crag search "Handler" -d .crag.db          # Search functions by name
crag risk -d .crag.db                      # Show high-risk functions
crag implements -d .crag.db                # Interface implementations
crag view -d .crag.db                      # Web UI visualization
crag export -d .crag.db -o crag.md         # Export as Markdown (RAG context)

Why crag?

	Text search (grep)	IDE (gopls)	crag
Interface calls	miss	partial	VTA precise resolution
Persisted & queryable	no	no	SQLite
AI integration	manual copy	no	MCP native
Incremental update	n/a	n/a	Git-aware
Zero CGO	n/a	n/a	Pure Go SQLite