ai-mind-map
v1.12.2
Published
AI Mind Map — MCP server that reduces AI coding agent token usage by 80-99% through persistent codebase memory, knowledge graphs, and intelligent context management
Maintainers
Readme
⚡ Install in One Command
npx ai-mind-map installAuto-detects Claude, Cursor, VS Code, Windsurf, Antigravity, Zed, Continue.dev — configures all of them instantly. No config files. No manual setup. Just run and restart your agent.
❓ The Problem
Every time an AI coding agent (Claude Code, Cursor, Copilot, Windsurf, Antigravity) processes a request, it re-reads your entire codebase from scratch. This wastes massive amounts of tokens:
Without AI Mind Map:
❌ Agent reads auth.ts → 5,000 tokens
❌ Agent reads auth.ts AGAIN → 5,000 tokens (same file!)
❌ Agent reads auth.ts AGAIN → 5,000 tokens (still the same file!)
Total: 15,000 tokens for 3 questions about ONE file
With AI Mind Map:
✅ mindmap_get_signature("authenticate") → 50 tokens
✅ mindmap_get_signature("validateToken") → 40 tokens
✅ mindmap_trace_dependencies("authenticate") → 100 tokens
Total: 190 tokens — that's a 99% reductionIndustry research shows ~42% of all tokens consumed by AI coding agents are avoidable waste — repeated file reads, re-discovering architecture, re-debating settled decisions.
✨ What AI Mind Map Does
AI Mind Map is an MCP (Model Context Protocol) server that gives your AI agent:
| Feature | What It Does | Token Savings | |---------|-------------|---------------| | 🗺️ Knowledge Graph | Parses your entire codebase into a queryable graph of functions, classes, and relationships | 99% | | 📝 Change Tracker | Knows exactly what changed since the AI's last session | 80% | | 🧠 Persistent Memory | Remembers architecture decisions, conventions, and context across sessions | 90% | | 🗜️ Smart Compression | Compresses build logs, test output, stack traces intelligently | 50-98% | | 📊 Progressive Loading | Loads only what's needed — signatures first, full code only when asked | 90% | | ⚡ Real-time Sync | File watcher keeps the graph updated as you code | Always fresh |
Inspired By The Best
This project combines proven techniques from:
| Source | Technique | Their Result | |--------|-----------|-------------| | codebase-memory-mcp | Knowledge Graph + SQLite | 99% reduction (120x fewer tokens) | | Aider | PageRank-based Repo Map | 90%+ reduction | | Mem0 | Persistent Memory with Decay | 3-4x cost reduction | | context-mode | Context Sandboxing + BM25 | 98% context reduction | | context-mem | Progressive Disclosure | 90%+ savings |
🚀 Quick Start
Method 1: npx (Fastest — Zero Install)
# Run directly without installing anything
npx ai-mind-map install
# That's it. It auto-detects Claude, Cursor, VS Code, Windsurf, Antigravity, Zed, Continue.devMethod 2: Global Install
npm install -g ai-mind-map
# Auto-detect and configure all your AI agents
ai-mind-map install
# Check everything is working
ai-mind-map doctorMethod 3: Clone (For Development)
git clone https://github.com/shdra06/ai-mind-map.git
cd ai-mind-map
npm install --legacy-peer-deps
npm run build
node dist/cli.js installWhat install Does
- ✅ Scans your system for AI coding agents (Claude, Cursor, VS Code, Windsurf, Antigravity, Zed, Continue.dev)
- ✅ Writes MCP config to each agent's config file
- ✅ Deploys rules files so agents know about our 41 tools
- ✅ Runs diagnostics to verify everything works
Verify It Works
ai-mind-map doctorOutput:
🩺 AI Mind Map — Diagnostics
────────────────────────────────────────────────────────
✔ Node.js v24.x (>= 18 required)
✔ SQLite In-memory test passed
✔ TypeScript Build dist/index.js exists
✔ Agents 3 detected, 3 configured🔌 Connect To Your AI Agent
Automatic (Recommended)
npx ai-mind-map installThis auto-detects all 7 agents and writes the config for you. Done.
What Gets Written
After running install, each agent's config file contains:
{
"mcpServers": {
"ai-mind-map": {
"command": "npx",
"args": ["-y", "ai-mind-map"]
}
}
}This tells the agent: "When you need MCP tools, run npx ai-mind-map". It downloads from npm on first use, then uses cache.
Manual Setup (If You Prefer)
If you want to configure manually, add this to your agent's config:
{
"mcpServers": {
"ai-mind-map": {
"command": "npx",
"args": ["-y", "ai-mind-map"]
}
}
}{
"mcpServers": {
"ai-mind-map": {
"command": "npx",
"args": ["-y", "ai-mind-map"]
}
}
}{
"mcp.servers": {
"ai-mind-map": {
"command": "npx",
"args": ["-y", "ai-mind-map"]
}
}
}{
"mcpServers": {
"ai-mind-map": {
"command": "npx",
"args": ["-y", "ai-mind-map"]
}
}
}{
"mcp.servers": {
"ai-mind-map": {
"command": "npx",
"args": ["-y", "ai-mind-map"]
}
}
}Command: npx
Args: -y ai-mind-map
Transport: stdio💡 After configuring, restart your AI agent so it picks up the new MCP server.
🔧 50+ MCP Tools
Once connected, your AI agent automatically gets all tools + a built-in guide telling it which tool to call first and when to use each one.
How AI Agents Discover Our Tools
AI Agent connects → Server sends 3 things:
1. ✅ instructions → "Call mindmap_session_resume FIRST" (auto-loaded)
2. ✅ tools/list → All 50 tools with descriptions + schemas (auto-loaded)
3. ✅ prompts/list → Interactive guides (on request)🌐 Client Compatibility
| Client | Works? | How AI Learns Our Tools |
|--------|:------:|------------------------|
| Claude Code / Desktop | ✅ | instructions + tools/list + prompts + rules file (CLAUDE.md) |
| Cursor | ✅ | tools/list + rules file (.cursorrules) |
| VS Code Copilot | ✅ | tools/list + rules file (.github/copilot-instructions.md) |
| Windsurf | ✅ | tools/list + rules file (.windsurfrules) |
| Antigravity (Gemini) | ✅ | tools/list + rules file (.agents/AGENTS.md) |
| Zed | ✅ | tools/list + MCP config |
| Continue.dev | ✅ | tools/list + MCP config |
| Any MCP client | ✅ | tools/list (universal MCP spec) |
| Ollama / LM Studio | ⚠️ | Not MCP clients natively — use via Continue.dev or Open WebUI |
| Codex (OpenAI) | ⚠️ | Not MCP natively — requires MCP bridge |
Key:
tools/listworks with every MCP client. Rules files (CLAUDE.md,.cursorrules, etc.) are deployed bynpx ai-mind-map installas a fallback for clients that don't honor theinstructionsfield.
⚡ Code Memory Engine (v1.4.0) — NEW
| Tool | What It Does | Token Savings |
|------|-------------|:---:|
| mindmap_session_resume ⭐⭐ | Resume from last session — returns what was worked on, what changed, project stats | 15-30K/session |
| mindmap_session_start | Start tracking a new AI coding task | — |
| mindmap_session_end | End session with summary for next agent | — |
| mindmap_changelog ⭐ | Symbol-level diffs — added/modified/deleted functions since a time | 20-50K/session |
| mindmap_hotspots | Most frequently changed files + symbols | 5-10K |
| mindmap_digest ⭐ | Full project summary in <2000 tokens | 10-25K/session |
| mindmap_file_digest ⭐ | Understand a file WITHOUT reading it | 3-10K/file |
| mindmap_verify | Hash-based content verification — check if cached code is still valid | 3-10K/file |
🗺️ Knowledge Graph (6)
| Tool | What It Does |
|------|-------------|
| mindmap_search | Search codebase by function/class name or free text |
| mindmap_get_structure | Project architecture overview in ~100 tokens |
| mindmap_trace_dependencies | Trace call chains — who calls what |
| mindmap_get_signature | Function signature without reading the file |
| mindmap_find_references | Find everywhere a symbol is used |
| mindmap_get_file_map | All symbols in a file with line ranges |
⭐ Smart Tools (3) — 99% Token Savings
| Tool | What It Does |
|------|-------------|
| mindmap_explain | Everything about a symbol in 1 call — signature, callers, callees, layer, blast radius, git history |
| mindmap_git_changes | Git-aware symbol-level diffs — which functions changed, who's impacted |
| mindmap_smart_search | Rich search — returns full context so AI never reads files |
🔍 Semantic Search (3)
| Tool | What It Does |
|------|-------------|
| mindmap_semantic_search | Search by meaning — "authentication", "error handling", "data validation" |
| mindmap_semantic_stats | Vocabulary size, index coverage |
| mindmap_synonyms | Programming synonym lookup |
📝 Change Tracking (3)
| Tool | What It Does |
|------|-------------|
| mindmap_what_changed | Summary of recent code changes |
| mindmap_session_diff | What changed since last AI session |
| mindmap_impact_analysis | Blast radius of a change |
🧠 Memory (5)
| Tool | What It Does |
|------|-------------|
| mindmap_recall | Retrieve relevant memories |
| mindmap_remember | Store a fact or convention |
| mindmap_get_decisions | Past architectural decisions |
| mindmap_decide | Record a new decision |
| mindmap_session_summary | Previous session summaries |
🔬 Advanced Analysis (7)
| Tool | What It Does |
|------|-------------|
| mindmap_query_graph | Cypher-like graph queries |
| mindmap_dead_code | Detect unused functions |
| mindmap_architecture | Full architecture overview |
| mindmap_get_code_snippet | Read source by symbol name |
| mindmap_search_code | Grep-like text search |
| mindmap_list_projects | List indexed projects |
| mindmap_health | System diagnostics |
🏗️ Flow Analysis (4)
| Tool | What It Does |
|------|-------------|
| mindmap_trace_flow | Trace behavioral flows through layers |
| mindmap_interaction_map | Full interaction map of the codebase |
| mindmap_classify_file | Classify a file's architectural layer |
| mindmap_layer_overview | Layer distribution overview |
🔍 Debug (3)
| Tool | What It Does |
|------|-------------|
| mindmap_debug_changes | Detailed change analysis |
| mindmap_file_before | File content before changes |
| mindmap_file_history | Full file change history |
🧬 Self-Evolving (3)
| Tool | What It Does |
|------|-------------|
| mindmap_teach | AI teaches new patterns — persists per-project |
| mindmap_get_learned | View all rules the system has learned |
| mindmap_forget | Remove a learned rule |
💻 CLI Commands
All commands work with npx (no install) or after global install (npm install -g ai-mind-map):
# Setup & Diagnostics
npx ai-mind-map install # Auto-configure all AI agents
npx ai-mind-map doctor # Check everything is working
npx ai-mind-map install --uninstall # Remove configs from all agents
# Index & Search
npx ai-mind-map index /path/to/project # Index a codebase
npx ai-mind-map search "authenticate" # Search the knowledge graph
npx ai-mind-map trace "processOrder" # Trace call chains
# Memory
npx ai-mind-map recall "authentication" # Recall past knowledge
npx ai-mind-map remember "We use JWT" # Store a convention
# Status
npx ai-mind-map status # Show index stats
npx ai-mind-map changes # Show recent changes⚙️ Configuration
Project-Level Config (Optional)
Create a .mindmap.json file in your project root to customize behavior:
{
"languages": ["typescript", "python", "javascript"],
"ignore": ["node_modules", "dist", "*.test.*", "coverage"],
"tokenBudgets": {
"graphResults": 2000,
"changeSummary": 1000,
"memoryRetrieval": 1500,
"fileContent": 3000,
"totalContext": 10000
},
"memory": {
"maxMemories": 500,
"decayRate": 0.95,
"importanceThreshold": 0.1,
"maxDecisions": 200
},
"compression": "moderate",
"watchEnabled": true
}CLI Options
node dist/index.js [options]
Options:
--project-root <path> Root of the project to index (default: auto-detect from git)
--db-path <path> SQLite database location (default: .mindmap/mindmap.db)
--log-level <level> debug | info | warn | error (default: info)🌐 Language Support
Tree-sitter AST parsing with automatic regex fallback:
| Language | AST Parsing | Regex Fallback | Extracts | |----------|:-----------:|:--------------:|----------| | JavaScript | ✅ | ✅ | Functions, classes, imports, exports | | TypeScript | ✅ | ✅ | + Interfaces, types, enums, decorators | | Python | ✅ | ✅ | Functions, classes, decorators, docstrings | | Java | ✅ | ✅ | Classes, methods, interfaces, annotations | | Go | ✅ | ✅ | Functions, structs, interfaces, methods | | Rust | ✅ | ✅ | Functions, structs, traits, impls, enums | | C/C++ | ✅ | ✅ | Functions, classes, structs, macros | | C# | ✅ | ✅ | Classes, methods, interfaces, properties | | Ruby | ✅ | ✅ | Classes, modules, methods, blocks | | PHP | ✅ | ✅ | Classes, functions, traits, namespaces | | Bash | ✅ | ✅ | Functions, variables, aliases | | CSS/HTML | ✅ | ✅ | Selectors, classes, IDs |
🏗️ Architecture
┌─────────────────────────────────────────────────────┐
│ AI Mind Map MCP Server │
│ │
│ ┌─────────────────┐ ┌────────────────┐ ┌────────┐ │
│ │ Knowledge Graph │ │ Change Tracker │ │ Memory │ │
│ │ ─────────────── │ │ ────────────── │ │ ────── │ │
│ │ Tree-sitter AST │ │ Chokidar Watch │ │ Mem0 │ │
│ │ SQLite + FTS5 │ │ Git Diff │ │ Style │ │
│ │ PageRank │ │ BM25 Search │ │ Decay │ │
│ └────────┬────────┘ └───────┬────────┘ └───┬────┘ │
│ │ │ │ │
│ ┌────────┴───────────────────┴────────────────┴────┐ │
│ │ Context Engine │ │
│ │ Content-Aware Compression (9 types) │ │
│ │ Progressive Disclosure (3 tiers) │ │
│ │ Token Budget Manager │ │
│ └──────────────────────┬────────────────────────────┘ │
│ │ │
│ 41 MCP Tools │
└─────────────────────────┼───────────────────────────────┘
│ stdio
┌─────────┴──────────┐
│ Your AI Agent │
│ Claude / Cursor / │
│ Copilot / Windsurf │
└────────────────────┘How the Memory System Works
AI Mind Map uses a three-tier memory architecture (inspired by cognitive science):
| Layer | What | Token Cost | Lifespan | |-------|------|-----------|----------| | Working Memory | Current task context | Full price | This conversation | | Episodic Memory | Session summaries, recent decisions | On-demand retrieval | Days to weeks | | Semantic Memory | Codebase graph, architecture, conventions | Queried, never dumped | Permanent (with decay) |
Memories have importance scores that:
- 📈 Increase when accessed (+0.1 per access, capped at 1.0)
- 📉 Decay over time (configurable, default 5% per day)
- 🗑️ Get pruned when importance drops below threshold
This means frequently-useful memories stick around, while stale ones naturally fade.
📊 Expected Token Savings
| Scenario | Without Mind Map | With Mind Map | Savings | |----------|:----------------:|:-------------:|:-------:| | Find a function signature | ~5,000 tokens | ~50 tokens | 99% | | Understand project structure | ~50,000 tokens | ~500 tokens | 99% | | Resume after session break | ~20,000 tokens | ~2,000 tokens | 90% | | Trace dependency chain | ~30,000 tokens | ~200 tokens | 99% | | Check what changed | ~10,000 tokens | ~500 tokens | 95% | | Compress build log | ~8,000 tokens | ~400 tokens | 95% |
🤝 Contributing
Contributions are welcome! Here's how:
- Fork the repo
- Create a feature branch:
git checkout -b feature/amazing-feature - Make your changes
- Run the build:
npm run build - Commit:
git commit -m "Add amazing feature" - Push:
git push origin feature/amazing-feature - Open a Pull Request
Development
# Watch mode (auto-recompile on changes)
npm run dev
# Type check without building
npx tsc --noEmit
# Run the server locally
node dist/index.js --project-root . --log-level debug📄 License
MIT — use it however you want. See LICENSE.
🙏 Acknowledgments
Built on the shoulders of giants:
- codebase-memory-mcp — Knowledge graph architecture (99% token reduction)
- Aider — Repository map with PageRank ranking
- Mem0 — Persistent memory with importance decay
- context-mode — Context sandboxing with BM25
- context-mem — Progressive disclosure patterns
- CocoIndex — Incremental AST indexing
- Repomix — Codebase compression techniques
- Tree-sitter — Multi-language AST parsing
- MCP Protocol — The standard that makes this possible
