Token Saver MCP

Token Saver MCP — AI as a Full-Stack Developer

Transform AI from a code suggester into a true full-stack developer — with instant access to code intelligence and real browser control.

📚 Full Usage Guide & Examples → |
📖 Detailed Technical README → |
🔄 Releases

🚀 What is Token Saver MCP?

Modern AI coding assistants waste enormous context (and your money) by stuffing full grep/search results into the model window. That leads to:

• ❌ Slow lookups (seconds instead of milliseconds)
• ❌ Thousands of wasted tokens per query
• ❌ AI “losing its train of thought” in cluttered context

Token Saver MCP fixes this.

It gives AI assistants direct access to VSCode’s Language Server Protocol (LSP) and the Chrome DevTools Protocol (CDP), so they can work like real developers:

• Instantly navigate & refactor code
• Run code in a real browser (Edge/Chrome)
• Test, debug, and verify changes themselves

Result: 90–99% fewer tokens, 100–1000× faster responses, and $200+ in monthly savings — while enabling AI to truly act as a full-stack engineer.

✨ Why Token Saver?

Think of your AI’s context window like a workbench. If it’s cluttered with logs, search dumps, and irrelevant snippets, the AI can’t focus.

Token Saver MCP keeps the workbench clean.

🔍 Without Token Saver

⚡ With Token Saver

Cleaner context = a sharper, more persistent AI assistant.

🏗️ Revolutionary Dual Architecture

Token Saver MCP uses a split architecture designed for speed and stability:

• 🏗️ VSCode Gateway Extension
  • Installed once, rarely updated
  • Exposes VSCode’s LSP via HTTP (port 9600)
• 🚀 Standalone MCP Server
  • Hot reloadable — no VSCode restarts
  • Language-agnostic (JS/TS, Python, Go, Rust…)
  • Bridges MCP protocol ↔ VSCode Gateway + CDP (port 9700 by default)

Why it matters: You can iterate on MCP tools instantly without rebuilding/restarting VSCode. Development is 60× faster and much more reliable.

🧰 What You Get

Token Saver MCP currently provides 40 production-ready tools across five categories:

• LSP Tools (14) → get_definition, get_references, rename_symbol, get_hover, find_implementations, …
• Memory Tools (9) → smart_resume (86-99% token savings vs /resume), write_memory, read_memory, search_memories (full-text search), export_memories, import_memories, …
• Browser Tools (8) → navigate_browser, execute_in_browser, take_screenshot, get_browser_console, …
• Testing Helpers (5) → test_react_component, test_api_endpoint, check_page_performance, …
• System Tools (4) → get_instructions, retrieve_buffer, get_supported_languages, …

📚 See the full Usage Guide with JSON examples →

📊 Proven Results

Token & Cost Savings (GPT-4 pricing):

• Tokens per search: 5,000 → 50
• Cost per search: $0.15 → $0.0015
• Typical dev workflow: $200+ saved per month

🌐 Browser Control (Edge-Optimized)

Beyond backend code, Token Saver MCP empowers AI to control a real browser through CDP:

• Launch Edge/Chrome automatically
• Click, type, navigate, capture screenshots
• Run frontend tests & debug JS errors in real-time
• Analyze performance metrics

Example workflow:

1. AI writes backend API (LSP tools)
2. AI launches browser & tests API (CDP tools)
3. AI sees error logs instantly
4. AI fixes backend code (LSP tools)
5. AI verifies fix in browser

➡️ No more “please test this manually” — AI tests itself.

🧠 Smart Memory System (NEW!)

Replace wasteful /resume commands with intelligent context restoration:

The Problem with /resume

• Dumps entire conversation history (5000+ tokens)
• Includes irrelevant tangents and discussions
• Costs $0.15+ per resume
• AI gets lost in the noise

The Solution: Smart Resume

Features:

• 86-99% token savings compared to /resume
• Progressive disclosure: Start minimal, expand as needed
• Full-text search: Find memories by content, not just keys
• Importance levels (1-5): Critical info persists, trivia can be dropped
• Verbosity levels (1-4): Control detail granularity
• Time-based filtering: Resume work from specific periods
• Export/Import: Backup and share memory contexts between sessions

Example:

Memory is stored locally in SQLite (~/.token-saver-mcp/memory.db) with automatic initialization.

🖥️ Real-Time Dashboard

Visit http://127.0.0.1:9700/dashboard to monitor:

• Server status & connection health
• Request metrics & response times
• Token & cost savings accumulating live
• Tool usage statistics

Perfect for seeing your AI’s efficiency gains in action.

⚡ Quickstart (30 Seconds)

That’s it! The installer:

• Finds open ports
• Creates config files
• Tests connection
• Provides the Claude/Gemini command

➡️ Full installation & build steps: Detailed README →

🔌 Supported AI Assistants

• Claude Code → works out of the box with MCP endpoint
• Gemini CLI → use /mcp-gemini endpoint
• Other AI tools → MCP JSON-RPC, streaming, or simple REST endpoints available

Endpoints include:

• http://127.0.0.1:9700/mcp (standard MCP)
• http://127.0.0.1:9700/mcp-gemini (Gemini)
• http://127.0.0.1:9700/mcp/simple (REST testing)
• http://127.0.0.1:9700/dashboard (metrics UI)

🔬 Verify It Yourself

Think the claims are too good to be true? Run the built-in test suite:

Expected output shows: hover, completions, definitions, references, diagnostics, semantic tokens, buffer management, etc. — all passing ✅

🛠️ Development

MCP server lives in /mcp-server/, with modular tools organized by category (lsp/, cdp/, helper/, system/).

See Full Technical README → for architecture diagrams, tool JSON schemas, buffer system details, and contributing guide.

📍 Roadmap / Vision

Token Saver MCP already unlocks full-stack AI workflows. Next up:

• 🔧 More browser automation tools (multi-tab, network control)
• 📦 Plugin ecosystem for custom toolpacks
• 🌐 Multi-assistant coordination (Claude + Gemini + others)
• 🧠 Expanded context management strategies

📄 License

MIT — free for personal and commercial use.

👉 Start today:

• Run ./mcp setup
• Tell your AI: “Use the get_instructions tool to understand Token Saver MCP.”
• Watch your AI become a focused, cost-efficient, full-stack developer.

📚 For in-depth details:

• Usage Guide & Examples
• Full Technical README