Structural code knowledge graph for AI coding assistants — impact analysis, cross-service flows, and symbol search via MCP
Project description
Grafio
Structural code knowledge graph for AI coding assistants.
Grafio indexes your codebase into a symbol-level graph and exposes it via MCP (Model Context Protocol) so AI assistants like Claude can understand cross-service flows, find callers, and analyze impact — without reading every file.
Install
pip install grafio # the daemon
npm install -g grafio-mcp # the MCP bridge for Claude Code
Quick start
# Start the daemon (auto-starts when Claude Code opens if grafio is on PATH)
grafio serve
# Index a repo
grafio index --repo-id my-project --root /path/to/my-project
Configure Claude Code — create ~/.claude/.mcp.json:
{
"mcpServers": {
"grafio": {
"command": "grafio-mcp",
"env": {
"GRAFIO_URL": "http://127.0.0.1:9742"
}
}
}
}
Restart Claude Code. Run /mcp to verify.
What it does
code_graph_context— understand a method + everything it calls across filescode_graph_impact— find what breaks if you change a symbolcode_graph_search— find symbols by name or REST endpoint pathcode_graph_update— incrementally reindex changed files
Claude automatically decides when to use Grafio vs Grep+Read based on the question.
Supported languages
Java, TypeScript, JavaScript, Python, Go, Rust
License
MIT
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