Semantic MCP tool discovery gateway - find tools by intent, not memory
Project description
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Tool Compass
Semantic navigator for MCP tools - Find the right tool by intent, not memory
95% fewer tokens. Find tools by describing what you want to do.
Installation • Usage • Docker • Performance • Contributing
The Problem
MCP servers expose dozens or hundreds of tools. Loading all tool definitions into context wastes tokens and slows down responses.
Before: 77 tools × ~500 tokens = 38,500 tokens per request
After: 1 compass tool + 3 results = ~2,000 tokens per request
Savings: 95%
The Solution
Tool Compass uses semantic search to find relevant tools from a natural language description. Instead of loading all tools, Claude calls compass() with an intent and gets back only the relevant tools.
Quick Start
Option 1: Local Installation
# Prerequisites: Ollama with nomic-embed-text
ollama pull nomic-embed-text
# Clone and setup
git clone https://github.com/mcp-tool-shop-org/tool-compass.git
cd tool-compass/tool_compass
# Create virtual environment
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Build the search index
python gateway.py --sync
# Run the MCP server
python gateway.py
# Or launch the Gradio UI
python ui.py
Option 2: Docker
# Clone the repo
git clone https://github.com/mcp-tool-shop-org/tool-compass.git
cd tool-compass/tool_compass
# Start with Docker Compose (requires Ollama running locally)
docker-compose up
# Or include Ollama in the stack
docker-compose --profile with-ollama up
# Access the UI at http://localhost:7860
Features
- Semantic Search - Find tools by describing what you want to do
- Progressive Disclosure -
compass()→describe()→execute() - Hot Cache - Frequently used tools are pre-loaded
- Chain Detection - Automatically discovers common tool workflows
- Analytics - Track usage patterns and tool performance
- Cross-Platform - Windows, macOS, Linux
- Docker Ready - One-command deployment
Architecture
┌─────────────────────────────────────────────────────────────┐
│ TOOL COMPASS │
│ │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ Ollama │ │ hnswlib │ │ SQLite │ │
│ │ Embedder │───▶│ HNSW │◀───│ Metadata │ │
│ │ (nomic) │ │ Index │ │ Store │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
│ │ │
│ ▼ │
│ ┌──────────────────┐ │
│ │ Gateway (9 tools)│ │
│ │ compass, describe│ │
│ │ execute, etc. │ │
│ └──────────────────┘ │
└─────────────────────────────────────────────────────────────┘
Usage
The compass() Tool
compass(
intent="I need to generate an AI image from a text description",
top_k=3,
category=None, # Optional: "file", "git", "database", "ai", etc.
min_confidence=0.3
)
Returns:
{
"matches": [
{
"tool": "comfy:comfy_generate",
"description": "Generate image from text prompt using AI",
"category": "ai",
"confidence": 0.912
}
],
"total_indexed": 44,
"tokens_saved": 20500,
"hint": "Found: comfy:comfy_generate. Use describe() for full schema."
}
Available Tools
| Tool | Description |
|---|---|
compass(intent) |
Semantic search for tools |
describe(tool_name) |
Get full schema for a tool |
execute(tool_name, args) |
Run a tool on its backend |
compass_categories() |
List categories and servers |
compass_status() |
System health and config |
compass_analytics(timeframe) |
Usage statistics |
compass_chains(action) |
Manage tool workflows |
compass_sync(force) |
Rebuild index from backends |
compass_audit() |
Full system report |
Configuration
| Variable | Description | Default |
|---|---|---|
TOOL_COMPASS_BASE_PATH |
Project root | Auto-detected |
TOOL_COMPASS_PYTHON |
Python executable | Auto-detected |
TOOL_COMPASS_CONFIG |
Config file path | ./compass_config.json |
OLLAMA_URL |
Ollama server URL | http://localhost:11434 |
COMFYUI_URL |
ComfyUI server | http://localhost:8188 |
See .env.example for all options.
Performance
| Metric | Value |
|---|---|
| Index build time | ~5s for 44 tools |
| Query latency | ~15ms (including embedding) |
| Token savings | ~95% (38K → 2K) |
| Accuracy@3 | ~95% (correct tool in top 3) |
Testing
# Run all tests
pytest
# Run with coverage
pytest --cov=. --cov-report=html
# Skip integration tests (no Ollama required)
pytest -m "not integration"
Troubleshooting
MCP Server Not Connecting
If Claude Desktop logs show JSON parse errors:
Unexpected token 'S', "Starting T"... is not valid JSON
Cause: print() statements corrupt JSON-RPC protocol.
Fix: Use logging or file=sys.stderr:
import sys
print("Debug message", file=sys.stderr)
Ollama Connection Failed
# Check Ollama is running
curl http://localhost:11434/api/tags
# Pull the embedding model
ollama pull nomic-embed-text
Index Not Found
python gateway.py --sync
Related Projects
Part of the Compass Suite for AI-powered development:
- File Compass - Semantic file search
- Integradio - Vector-embedded Gradio components
- Backpropagate - Headless LLM fine-tuning
- Comfy Headless - ComfyUI without the complexity
Contributing
We welcome contributions! See CONTRIBUTING.md for guidelines.
Security
For security vulnerabilities, please see SECURITY.md. Do not open public issues for security bugs.
Support
- Questions / help: Discussions
- Bug reports: Issues
- Security: SECURITY.md
License
MIT - see LICENSE file for details.
Credits
- HNSW: Malkov & Yashunin, "Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs" (2016)
- nomic-embed-text: Nomic AI's open embedding model
- FastMCP: Anthropic's MCP framework
- Gradio: Hugging Face's ML web framework
"Syntropy above all else."
Tool Compass reduces entropy in the MCP ecosystem by organizing tools by semantic meaning.
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