🧠 Make Your AI Coding Assistant 500x Smarter — Complete Guide to graphify + code-review-graph + MCP (Knowledge Graphs for Claude Code, Cursor, Windsurf)

To dramatically improve AI coding assistants by using the Model Context Protocol (MCP) to create knowledge graphs of codebases. Instead of having the AI read every file from scratch for each query—which is slow and expensive—the guide shows how to install and configure tools like `graphify` and `code-review-graph` to build a map of code relationships. Using this approach reduces token consumption by up to 500x, allowing the AI to answer questions in seconds by querying the graph rather than scanning the entire project.

<div align="center" 🧠 Make Your AI Coding Assistant 500x Smarter Stop Burning Tokens — Use Knowledge Graphs + MCP to Give AI a Map of Your Code <img src="https://readme-typing-svg.herokuapp.com?font=Fira+Code&weight=600&size=20&pause=1000&color=00D4AA&center=true&vCenter=true&width=700&lines=500x+fewer+tokens+per+query;AI+reads+a+graph+instead+of+your+entire+codebase;Auto-updates+on+every+git+commit;Works+with+Claude+Code%2C+Cursor%2C+Windsurf;Zero+config+after+setup+%E2%80%94+fully+automatic" alt="Typing SVG" / <br/ graphify https://img.shields.io/badge/graphify-Knowledge Graph-00D4AA?style=for-the-badge https://pypi.org/project/graphifyy/ code-review-graph https://img.shields.io/badge/code--review--graph-AST MCP Server-FF6F00?style=for-the-badge https://pypi.org/project/code-review-graph/ MCP https://img.shields.io/badge/MCP-Model Context Protocol-7F52FF?style=for-the-badge https://modelcontextprotocol.io Claude Code https://img.shields.io/badge/Claude Code-Compatible-E8590C?style=for-the-badge https://claude.ai/code Cursor https://img.shields.io/badge/Cursor-Compatible-000000?style=for-the-badge https://cursor.sh </div --- 📖 What This Guide Covers Your AI assistant reads your ENTIRE codebase every time you ask a question. That's slow, expensive, and dumb. This guide gives your AI a MAP of your code — so it looks up answers instead of reading everything from scratch. ┌──────────────────────────────────┐ │ 1. What is MCP? │ ← The "USB port" for AI │ 2. Install graphify │ ← Builds the knowledge graph │ 3. Install code-review-graph │ ← Fast code-only MCP server │ 4. Connect via MCP │ ← Wire it to Claude Code │ 5. Automate updates │ ← Graph stays fresh forever │ 6. Use it │ ← 500x less tokens └──────────────────────────────────┘ --- 🤔 Wait, What is MCP? MCP = Model Context Protocol Think of it like a USB port for AI . USB lets ANY device talk to ANY computer: 🖨️ Printer ──┐ 📷 Camera ──┤── USB ──── 💻 Computer 🎮 Gamepad ──┘ MCP lets ANY tool talk to ANY AI assistant: 📊 Graph DB ──┐ 💬 Slack ──┤── MCP ──── 🤖 AI Assistant 📁 Code Graph ──┘ Without MCP: You: "How does LlmRouter work?" AI: "Let me read... reads 143 files ... burns 362,000 tokens ... here's what I found" ⏱️ 30 seconds 💰 $$$ tokens burned With MCP: You: "How does LlmRouter work?" AI: "Let me check the graph..." → query graph "callers of", "LlmRouter" → gets back 10 precise connections in 0.2 seconds "LlmRouter has 47 connections. It's called by WebChatServer, ZeroClawService..." ⏱️ 2 seconds 💰 ~700 tokens that's 500x less The Restaurant Analogy 🍕 WITHOUT MCP reading files : ┌──────────────────────────────────────────┐ │ │ │ You walk into a restaurant. │ │ There's no menu. │ │ You go to the kitchen. │ │ You open EVERY fridge. │ │ You read EVERY ingredient label. │ │ Then you decide what to order. │ │ │ │ That's your AI reading your codebase. │ │ │ └──────────────────────────────────────────┘ WITH MCP using graph : ┌──────────────────────────────────────────┐ │ │ │ You walk into a restaurant. │ │ There's a MENU on the table. │ │ You pick what you want. │ │ Done. │ │ │ │ The graph IS the menu. │ │ MCP IS the waiter. │ │ │ └──────────────────────────────────────────┘ --- 🧩 The Two Tools And Why You Need Both ┌─────────────────────────────────────────────────────────────────┐ │ │ │ graphify code-review-graph │ │ ════════ ═════════════════ │ │ │ │ 📚 The FULL picture ⚡ The FAST picture │ │ │ │ ✅ Code functions, classes ✅ Code functions, classes │ │ ✅ Docs README, guides ❌ No docs │ │ ✅ Images screenshots ❌ No images │ │ ✅ Bugs & plans ❌ No docs │ │ ✅ Semantic connections ❌ Only structural │ │ ✅ Community clusters ❌ Basic clusters │ │ ✅ Interactive HTML viz ✅ HTML viz │ │ │ │ 🐌 Needs LLM for docs/images ⚡ Pure AST, no LLM needed │ │ 📊 1,479 nodes example 📊 1,411 nodes example │ │ │ │ Best for: Best for: │ │ "How does feature X relate "Who calls this function?" │ │ to the bug in BUGS.md?" "What imports this class?" │ │ "Impact of changing this?" │ │ │ └─────────────────────────────────────────────────────────────────┘ USE BOTH. They complement each other. code-review-graph = your quick dictionary graphify = your full encyclopedia --- 📦 Step 1 — Install Everything 1a. Install graphify bash pip install graphifyy Yes, it's graphifyy with two y's on PyPI. 1b. Install code-review-graph bash pip install code-review-graph 1c. Verify both installed bash graphify --version code-review-graph --help You should see version info and help text. If not, make sure Python is in your PATH. --- 🔨 Step 2 — Build Your First Graph 2a. Build the graphify knowledge graph Navigate to your project root and run: bash cd /path/to/your/project Then in Claude Code or any AI assistant with graphify skill : /graphify . This will: 1. Detect all files code, docs, images 2. Parse code via AST free, no LLM 3. Extract concepts from docs/images uses LLM 4. Build a graph with nodes + edges 5. Cluster into communities 6. Generate graphify-out/graph.html interactive viz What happens: Your Project graphify-out/ ├── src/ ├── graph.json ← The graph data │ ├── auth.kt ──────► ├── graph.html ← Open in browser │ ├── router.kt ──────► ├── GRAPH REPORT.md ← Audit report │ └── database.kt ──────► └── cost.json ← Token usage ├── README.md ──────► ├── BUGS.md ──────► └── screenshots/ ──────► All files become graph nodes with edges showing relationships 2b. Build the code-review-graph bash code-review-graph build This is instant — it only parses code via AST no LLM needed : $ code-review-graph build INFO: Progress: 50/140 files parsed INFO: Progress: 100/140 files parsed INFO: Progress: 140/140 files parsed Full build: 140 files, 1411 nodes, 2801 edges 2c. Open the graph in your browser bash graphify interactive visualization open graphify-out/graph.html macOS start graphify-out/graph.html Windows xdg-open graphify-out/graph.html Linux You'll see something like this: ┌─────────────────────────────────────────────┐ │ │ │ ○ LlmRouter │ │ /|\ │ │ / | \ │ │ ○ ○ ○ WebChat KeyManager ToolSystem │ │ | | | │ │ ○ ○ ○ Service Agents OfflineModel │ │ │ │ Nodes colored by community │ │ Click any node to see connections │ │ Zoom, pan, drag │ │ │ └─────────────────────────────────────────────┘ --- 🔌 Step 3 — Connect to Your AI via MCP What are we doing here? Right now: Claude Code ──── ??? ──── Your graph can't see the graph After this step: Claude Code ──── MCP ──── code-review-graph server ──── Fast code lookups │ └────────── MCP ──── graphify server ──────────── Full knowledge graph 3a. Create .mcp.json in your project root Create a file called .mcp.json note the dot in your project's root directory: json { "mcpServers": { "code-review-graph": { "command": "code-review-graph", "args": "serve" , "type": "stdio" }, "graphify": { "command": "python", "args": "-m", "graphify.serve", "graphify-out/graph.json" , "type": "stdio" } } } That's it. Claude Code reads .mcp.json on startup and connects to both servers automatically. 3b. What each server provides code-review-graph MCP tools: | Tool | What it does | Example | |------|-------------|---------| | semantic search nodes | Find code by keyword | "Find all auth-related classes" | | query graph | Trace relationships | "Who calls LlmRouter?" | | get impact radius | Blast radius of a change | "What breaks if I change this?" | | detect changes | Risk-scored code review | "Review my last commit" | | get review context | Token-efficient snippets | "Show me relevant code for review" | | get affected flows | Execution path analysis | "Which flows does this change affect?" | graphify MCP tools: | Tool | What it does | Example | |------|-------------|---------| | query graph | Search the full graph | "How does auth relate to the API?" | | get node | Get node details | "Tell me about OfflineModelManager" | | get neighbors | Find connected nodes | "What's connected to LlmRouter?" | | get community | See a cluster | "Show me the memory subsystem" | | god nodes | Most connected nodes | "What are the core abstractions?" | | graph stats | Graph overview | "How big is the graph?" | | shortest path | Find path between concepts | "How does auth connect to database?" | 3c. Restart Claude Code bash Close and reopen Claude Code, or start a new session The MCP servers will connect automatically 3d. Verify it works In your new Claude Code session, ask: "What are the most connected nodes in this codebase?" If it uses MCP tools you'll see tool calls like god nodes or semantic search nodes instead of running Grep/Read on your files — it's working BEFORE MCP what you DON'T want to see : ┌────────────────────────────────────────┐ │ 🔍 Grep "class. Router", / .kt │ ← Reading files │ 📖 Read src/LlmRouter.kt │ ← Reading files │ 📖 Read src/ProviderRouter.kt │ ← Reading files │ 📖 Read src/WebChatServer.kt │ ← More files... │ │ │ 💰 Used: ~50,000 tokens │ └────────────────────────────────────────┘ AFTER MCP what you WANT to see : ┌────────────────────────────────────────┐ │ 🔌 query graph "callers of", │ ← Graph lookup │ "LlmRouter" │ │ │ │ 💰 Used: ~700 tokens │ └────────────────────────────────────────┘ --- 🤖 Step 4 — Automate Everything Set and Forget This is the magic part. After this, your graphs update themselves every time you commit code. 4a. Install the graphify git hook bash graphify hook install Output: post-commit: appended to .git/hooks/post-commit post-checkout: appended to .git/hooks/post-checkout 4b. Add code-review-graph to the same hook Open .git/hooks/post-commit and add at the bottom: bash code-review-graph: incremental update for MCP server if command -v code-review-graph /dev/null 2 &1; then code-review-graph update 2 /dev/null || true fi 4c. What happens now on every commit You type: git commit -m "add new feature" ┌──────────────┐ │ git commit │ └──────┬───────┘ │ ┌──────▼───────┐ │ post-commit │ │ hook │ └──────┬───────┘ │ ┌────────────┼────────────┐ ▼ ▼ ┌─────────────────┐ ┌──────────────────────┐ │ graphify │ │ code-review-graph │ │ │ │ │ │ Re-extracts only │ │ Re-parses only │ │ CHANGED files │ │ CHANGED files │ │ AST, no LLM │ │ AST, no LLM │ │ │ │ │ │ Updates: │ │ Updates: │ │ graph.json │ │ internal graph │ │ GRAPH REPORT.md │ │ MCP serves new data │ └─────────────────┘ └──────────────────────┘ ⚡ Both take < 5 seconds for code-only changes ⚡ No LLM tokens consumed ⚡ No internet needed ⚡ Completely automatic 4d. What about docs and images? Code changes auto-update AST parsing, free . Docs/images need LLM — run manually when you update docs: bash /graphify . --update This only re-extracts new/changed files cached results are reused : $ /graphify . --update Cache: 165 files hit, 2 files need extraction Semantic extraction: ~2 files → 1 agent, estimated ~45s ...done 4e. Manual update no commit needed Don't want to commit just to update the graph? Run these anytime: bash Update code-review-graph instant, no LLM code-review-graph update Or full rebuild from scratch code-review-graph build For graphify, in Claude Code: /graphify . --update ┌──────────────────────────────────────────────────────────────┐ │ │ │ HOW THE GRAPH STAYS FRESH │ │ │ │ Option 1: Automatic git commit │ │ ════════════════════════════════ │ │ git commit → hook runs → both graphs update │ │ You do nothing. It just works. │ │ │ │ Option 2: Manual anytime │ │ ═════════════════════════ │ │ code-review-graph update ← run in terminal │ │ /graphify . --update ← run in Claude Code │ │ No commit needed. Run after any edit. │ │ │ │ Option 3: Full rebuild switch branch, big changes │ │ ═════════════════════════════════════════════════ │ │ code-review-graph build ← rebuild from scratch │ │ /graphify . ← full rebuild in Claude Code │ │ │ └──────────────────────────────────────────────────────────────┘ Summary: What's automatic vs manual | Change Type | Auto-updates? | Cost | |-------------|:------------:|------| | New .kt / .java / .py file | ✅ On commit | Free AST | | Modified code file | ✅ On commit | Free AST | | New/changed .md / .txt doc | ❌ Manual: /graphify . --update | LLM tokens | | New screenshot / image | ❌ Manual: /graphify . --update | LLM tokens | --- 📊 Step 5 — See the Token Savings After graphify builds, it prints a benchmark: graphify token reduction benchmark ────────────────────────────────────────────────── Corpus: 271,756 words → ~362,341 tokens naive Graph: 1,479 nodes, 1,326 edges Avg query cost: ~706 tokens Reduction: 513.2x fewer tokens per query Per question: 787.7x how does authentication work 469.4x what is the main entry point 332.1x how are errors handled 827.3x what connects the data layer to the api 469.4x what are the core abstractions What does 500x mean in practice? Without graph: 10 questions × 362,341 tokens = 3,623,410 tokens 💰 ~$10-15 in API costs With graph: 10 questions × 706 tokens = 7,060 tokens 💰 ~$0.02 in API costs That's like paying $0.02 instead of $10. For the SAME answers. Actually BETTER answers structural context . --- 🎯 Real Usage Examples Example 1: "What does LlmRouter do?" WITHOUT graph: AI reads LlmRouter.kt 500 lines AI reads every file that imports it 20+ files AI reads docs mentioning it Total: ~50,000 tokens, 30 seconds WITH graph: AI calls: get node "LlmRouter" AI calls: get neighbors "LlmRouter" Gets back: 47 connections, callers, callees, related docs Total: ~700 tokens, 2 seconds Example 2: "What breaks if I change OfflineModelManager?" WITHOUT graph: AI greps for "OfflineModelManager" in all files AI reads each file to understand the dependency AI guesses at impact Total: ~30,000 tokens, maybe misses indirect deps WITH graph: AI calls: get impact radius "OfflineModelManager" Gets back: direct deps, transitive deps, affected flows, test coverage Total: ~500 tokens, complete picture Example 3: "Review my last commit" WITHOUT graph: AI reads the diff AI reads surrounding code for context AI reads test files Total: ~40,000 tokens WITH graph: AI calls: detect changes Gets back: risk score, affected communities, missing test coverage AI calls: get review context for only the risky parts Total: ~2,000 tokens, better review --- 🗂️ Project Structure After Setup your-project/ ├── .mcp.json ← MCP server config commit this ├── .gitignore ← Add: graphify-out/ ├── .git/hooks/post-commit ← Auto-update hook ├── graphify-out/ ← ⚠️ GITIGNORED │ ├── graph.json ← The knowledge graph │ ├── graph.html ← Interactive visualization │ ├── GRAPH REPORT.md ← Audit report god nodes, surprises │ └── cost.json ← Token usage tracker ├── src/ │ └── ... your code ... └── README.md What to commit, what to gitignore | File | Commit? | Why | |------|:-------:|-----| | .mcp.json | ✅ Yes | Team members get MCP servers too | | graphify-out/ | ❌ No | Generated, can be rebuilt | | .git/hooks/ | ❌ No | Local only each dev runs graphify hook install | Add to your .gitignore : Knowledge graph outputs rebuild with: /graphify . graphify-out/ --- 🚀 Quick Start — Set Up ANY Project in 2 Minutes Copy-paste these commands in your project root: bash 1. Install one-time, works for all projects pip install graphifyy code-review-graph 2. Build the code-review-graph instant, no LLM code-review-graph build 3. Create MCP config for your AI editor cat .mcp.json << 'EOF' { "mcpServers": { "code-review-graph": { "command": "code-review-graph", "args": "serve" , "type": "stdio" }, "graphify": { "command": "python", "args": "-m", "graphify.serve", "graphify-out/graph.json" , "type": "stdio" } } } EOF 4. Install auto-update git hooks graphify hook install 5. Add code-review-graph to the same hook cat .git/hooks/post-commit << 'HOOK' code-review-graph: incremental update for MCP server if command -v code-review-graph /dev/null 2 &1; then code-review-graph update 2 /dev/null || true fi HOOK 6. Gitignore the output echo -e "\n Knowledge graph outputs\ngraphify-out/" .gitignore 7. Auto-configure your AI editor pick ONE : graphify claude install Claude Code graphify cursor install Cursor graphify gemini install Gemini CLI / Android Studio Gemini graphify antigravity install Google Antigravity graphify codex install OpenAI Codex graphify copilot install GitHub Copilot CLI graphify opencode install OpenCode graphify aider install Aider graphify droid install Factory Droid graphify claw install OpenClaw graphify trae install Trae graphify trae-cn install Trae CN 8. Build the graphify knowledge graph In Claude Code , just type: /graphify . This is a Claude Code skill slash command . It reads all your code, docs, and images, then builds the full knowledge graph. Not using Claude Code? You can still build the code graph no LLM needed : bash code-review-graph build This gives you the AST-based graph with MCP. The full graphify graph with docs/images/semantic connections requires /graphify . in Claude Code or another AI editor with the graphify skill installed. 9. Start a new session Close and reopen your AI editor. The MCP servers load on startup. Done ┌────────────────────────────────────────────────────┐ │ │ │ ✅ code-review-graph MCP → code lookups │ │ ✅ graphify MCP → full knowledge graph│ │ ✅ git hook → auto-updates │ │ ✅ CLAUDE.md / .cursorrules → AI knows to use it │ │ │ │ Your AI is now 500x smarter. For every project. │ │ │ └────────────────────────────────────────────────────┘ --- 🔄 Setting Up Your NEXT Project Already did the Quick Start once? For each new project, it's even faster: bash cd /path/to/new/project Build + configure 30 seconds code-review-graph build graphify hook install graphify claude install or: cursor, gemini, antigravity, codex, copilot, etc. Create MCP config cat .mcp.json << 'EOF' { "mcpServers": { "code-review-graph": { "command": "code-review-graph", "args": "serve" , "type": "stdio" }, "graphify": { "command": "python", "args": "-m", "graphify.serve", "graphify-out/graph.json" , "type": "stdio" } } } EOF echo -e "\ngraphify-out/" .gitignore Add code-review-graph to hook cat .git/hooks/post-commit << 'HOOK' if command -v code-review-graph /dev/null 2 &1; then code-review-graph update 2 /dev/null || true fi HOOK Then in Claude Code: /graphify . That's it — 30 seconds per project after the first time. --- 🌐 Multi-Project Setup — Query ALL Your Projects From ONE Session <div align="center" Multi-Project https://img.shields.io/badge/Multi--Project-Query All From Anywhere-FF6F00?style=for-the-badge . Global MCP https://img.shields.io/badge/Global MCP-Works In Every Session-00D4AA?style=for-the-badge . </div 💡 The Problem: You graphified Project A and Project B separately. But when you open Claude Code in Project A, it only sees Project A's graph. How do you query both? ✅ The Solution: Set MCP servers globally so they're available in EVERY session, from ANY folder. 🤔 Local vs Global — What's the Difference? LOCAL .mcp.json in project folder GLOBAL ~/.claude.json in home folder ═══════════════════════════════════ ════════════════════════════════════ 📁 Project-A/ 🏠 ~/.claude.json │ └── .mcp.json │ │ └── graphify-A ✅ ├── graphify-A ✅ │ ├── graphify-B ✅ 📁 Project-B/ └── graphify-C ✅ │ └── .mcp.json │ └── graphify-B ✅ Open Claude Code ANYWHERE: │ → ALL graphs available ✅ Open Claude Code in Project-A: → Only sees graphify-A ❌ → Can't query Project-B ❌ 🚀 Step 1 — Graphify Each Project First bash Project A cd /path/to/project-A code-review-graph build In Claude Code: /graphify . Project B cd /path/to/project-B code-review-graph build In Claude Code: /graphify . Project C ... repeat for each project 🔗 Step 2 — Register All Projects in code-review-graph bash code-review-graph has BUILT-IN multi-repo support 🎉 code-review-graph register "/path/to/project-A" --alias projectA code-review-graph register "/path/to/project-B" --alias projectB code-review-graph register "/path/to/project-C" --alias projectC Check what's registered code-review-graph repos ┌──────────────────────────────────────────────────────────┐ │ │ │ $ code-review-graph repos │ │ │ │ ✅ projectA → /path/to/project-A 1,411 nodes │ │ ✅ projectB → /path/to/project-B 892 nodes │ │ ✅ projectC → /path/to/project-C 2,100 nodes │ │ │ │ ONE MCP server. ALL projects. 🔥 │ │ │ └──────────────────────────────────────────────────────────┘ 🎯 That's it for code-review-graph The single code-review-graph serve MCP server now queries ALL registered repos automatically. 🧠 Step 3 — Set graphify MCP Globally For graphify, add each project's graph server to your global ~/.claude.json : Tell your AI assistant: "Set up global MCP servers for all my graphified projects" Or manually add to ~/.claude.json : json { "mcpServers": { "code-review-graph": { "command": "code-review-graph", "args": "serve" , "type": "stdio" }, "graphify-projectA": { "command": "python", "args": "-m", "graphify.serve", "/path/to/project-A/graphify-out/graph.json" }, "graphify-projectB": { "command": "python", "args": "-m", "graphify.serve", "/path/to/project-B/graphify-out/graph.json" }, "graphify-projectC": { "command": "python", "args": "-m", "graphify.serve", "/path/to/project-C/graphify-out/graph.json" } } } ⚠️ Important: Each graphify server needs a unique name graphify-projectA , graphify-projectB , etc. ✅ Result — Everything Connected ┌──────────────────────────────────────────────────────────────────┐ │ │ │ 🌐 OPEN CLAUDE CODE FROM ANY FOLDER │ │ │ │ ┌─────────────────┐ │ │ │ Claude Code │ │ │ │ any folder │ │ │ └────────┬────────┘ │ │ │ │ │ Global MCP Servers Load Automatically │ │ │ │ │ ┌───────────────────┼───────────────────┐ │ │ │ │ │ │ │ ▼ ▼ ▼ │ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │ │ 📱 Project A │ │ 🌐 Project B │ │ 🎮 Project C │ │ │ │ │ │ │ │ │ │ │ │ graphify-A │ │ graphify-B │ │ graphify-C │ │ │ │ code-review │ │ code-review │ │ code-review │ │ │ │ │ │ │ │ │ │ │ │ 1,411 nodes │ │ 892 nodes │ │ 2,100 nodes │ │ │ └──────────────┘ └──────────────┘ └──────────────┘ │ │ │ │ 🔍 "How does auth work in Project A?" → queries graphify-A │ │ 🔍 "Compare Project B's DB to C's" → queries both B and C │ │ 🔍 "Impact of changing this class?" → queries code-review │ │ │ │ ALL PROJECTS. ANY SESSION. ZERO SETUP PER SESSION. │ │ │ └──────────────────────────────────────────────────────────────────┘ 📊 Quick Reference ┌─────────────────────┬──────────────────────┬────────────────────────┐ │ Tool │ Multi-Project How? │ Where to Configure │ ├─────────────────────┼──────────────────────┼────────────────────────┤ │ │ │ │ │ code-review-graph │ Built-in │ code-review-graph │ │ │ register command │ register <path │ │ │ 1 server = N repos │ │ │ │ │ │ │ graphify │ 1 server per │ ~/.claude.json │ │ │ project │ global mcpServers │ │ │ unique name each │ │ │ │ │ │ └─────────────────────┴──────────────────────┴────────────────────────┘ 💡 Pro tip: After graphifying a new project, just add one more graphify-newproject entry to ~/.claude.json and restart Claude Code. That's it — the new project is connected to all your sessions. --- ❓ FAQ Q: Does this work with Cursor / Windsurf / other AI editors? Yes graphify supports 12 AI editors/agents out of the box: ┌──────────────────────────────────────────────────────────────────────┐ │ │ │ EDITOR / AGENT INSTALL COMMAND WHAT IT WRITES │ │ ═══════════════ ═══════════════ ══════════════ │ │ │ │ Claude Code graphify claude install CLAUDE.md │ │ Cursor graphify cursor install .cursorrules │ │ Gemini CLI / Android Studio graphify gemini install GEMINI.md │ │ Google Antigravity graphify antigravity install .agent/ │ │ OpenAI Codex graphify codex install AGENTS.md │ │ GitHub Copilot CLI graphify copilot install ~/.copilot/ │ │ OpenCode graphify opencode install AGENTS.md │ │ Aider graphify aider install AGENTS.md │ │ Factory Droid graphify droid install AGENTS.md │ │ OpenClaw graphify claw install AGENTS.md │ │ Trae graphify trae install AGENTS.md │ │ Trae CN graphify trae-cn install AGENTS.md │ │ │ └──────────────────────────────────────────────────────────────────────┘ MCP is a standard protocol. The .mcp.json config works with any editor that supports MCP. Android Studio users: If you use Gemini in Android Studio, run graphify gemini install . The MCP config .mcp.json is project-level so the code-review-graph server is available too. Q: What languages are supported? code-review-graph: Kotlin, Java, Python, TypeScript, JavaScript, Go, Rust, C/C++, Ruby, Swift, Scala, PHP, Lua — anything with AST parsing. graphify: ALL files. Code via AST, docs/images via LLM semantic extraction. Q: Does this cost money? - code-review-graph: 100% free. Pure AST parsing, no LLM. - graphify AST extraction: Free. No LLM needed for code files. - graphify semantic extraction: Uses your AI tokens for docs/images only. One-time cost, then cached. - Auto-updates on commit: Free AST only for code changes . Q: My graph is out of date after switching branches bash code-review-graph build rebuild from scratch instant Then in Claude Code: /graphify . --update incremental update only changed files Q: Can I query the graph without Claude Code? Yes graphify has a built-in CLI: bash graphify query "how does authentication work?" graphify query "how does authentication work?" --dfs depth-first trace graphify query "how does authentication work?" --budget 1500 limit tokens And in Claude Code, you can use slash commands: /graphify query "how does authentication work?" /graphify path "AuthModule" "Database" /graphify explain "LlmRouter" Q: How big can the graph get? Tested with 1,500+ nodes and 2,800+ edges without issues. The HTML visualization handles up to 5,000 nodes. Beyond that, use Obsidian vault /graphify . --obsidian . --- 🔧 Troubleshooting | Problem | Fix | |---------|-----| | graphify: command not found | pip install graphifyy two y's | | code-review-graph: command not found | pip install code-review-graph | | MCP tools not showing in Claude Code | Restart session MCP loads at startup | | Graph out of date | Run code-review-graph build + in Claude Code: /graphify . --update | | UnicodeEncodeError on Windows | Set PYTHONUTF8=1 environment variable | | HTML viz won't open | Try: python -m http.server 8080 in graphify-out/ , open localhost:8080/graph.html | | Hook not running on commit | Check: ls -la .git/hooks/post-commit must be executable | | Graph was built on different branch | Run code-review-graph build to rebuild | --- 🎁 Bonus: The Full Picture ┌──────────────────────────────────────────────────────────────────┐ │ │ │ YOUR DEVELOPMENT WORKFLOW │ │ │ │ ┌──────────┐ ┌──────────┐ ┌──────────┐ │ │ │ Write │────►│ Commit │────►│ Hook │ │ │ │ Code │ │ git │ │ Runs │ │ │ └──────────┘ └──────────┘ └─────┬────┘ │ │ │ │ │ ┌─────────────┼─────────────┐ │ │ ▼ ▼ │ │ ┌────────────────┐ ┌─────────────────┐ │ │ │ graphify │ │ code-review- │ │ │ │ updates │ │ graph updates │ │ │ │ graph.json │ │ internal graph │ │ │ └───────┬────────┘ └────────┬────────┘ │ │ │ │ │ │ ▼ ▼ │ │ ┌────────────────┐ ┌─────────────────┐ │ │ │ graphify │ │ code-review- │ │ │ │ MCP server │ │ graph MCP │ │ │ │ full graph │ │ server fast │ │ │ └───────┬────────┘ └────────┬────────┘ │ │ │ │ │ │ └──────────┬───────────────┘ │ │ │ │ │ ▼ │ │ ┌────────────────┐ │ │ │ Claude Code │ │ │ │ / Cursor / │ │ │ │ Any AI Editor │ │ │ └────────────────┘ │ │ │ │ │ ▼ │ │ ┌────────────────┐ │ │ │ 500x FASTER │ │ │ │ 500x CHEAPER │ │ │ │ BETTER ANSWERS│ │ │ └────────────────┘ │ │ │ └──────────────────────────────────────────────────────────────────┘ --- <div align="center" Made with 🧠 by Ashok Varma Matta https://github.com/ashokvarmamatta If this saved you time, star the gist and share it with your team graphify https://img.shields.io/badge/graphify-GitHub-00D4AA?style=flat-square https://github.com/graphify-ai/graphify code-review-graph https://img.shields.io/badge/code--review--graph-PyPI-FF6F00?style=flat-square https://pypi.org/project/code-review-graph/ </div