Implement comprehensive system for handling very large documentation sites with intelligent splitting strategies and router/hub architecture. **New CLI Tools:** - cli/split_config.py: Split large configs into focused sub-skills * Strategies: auto, category, router, size * Configurable target pages per skill (default: 5000) * Dry-run mode for preview - cli/generate_router.py: Create intelligent router/hub skills * Auto-generates routing logic based on keywords * Creates SKILL.md with topic-to-skill mapping * Infers router name from sub-skills - cli/package_multi.py: Batch package multiple skills * Package router + all sub-skills in one command * Progress tracking for each skill **MCP Integration:** - Added split_config tool (8 total MCP tools now) - Added generate_router tool - Supports 40K+ page documentation via MCP **Configuration:** - New split_strategy parameter in configs - split_config section for fine-tuned control - checkpoint section for resume capability (ready for Phase 4) - Example: configs/godot-large-example.json **Documentation:** - docs/LARGE_DOCUMENTATION.md (500+ lines) * Complete guide for 10K+ page documentation * All splitting strategies explained * Detailed workflows with examples * Best practices and troubleshooting * Real-world examples (AWS, Microsoft, Godot) **Features:** ✅ Handle 40K+ page documentation efficiently ✅ Parallel scraping support (5x-10x faster) ✅ Router + sub-skills architecture ✅ Intelligent keyword-based routing ✅ Multiple splitting strategies ✅ Full MCP integration 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
Skill Seeker MCP Server
Model Context Protocol (MCP) server for Skill Seeker - enables Claude Code to generate documentation skills directly.
What is This?
This MCP server allows Claude Code to use Skill Seeker's tools directly through natural language commands. Instead of running CLI commands manually, you can ask Claude Code to:
- Generate config files for any documentation site
- Estimate page counts before scraping
- Scrape documentation and build skills
- Package skills into
.zipfiles - List and validate configurations
Quick Start
1. Install Dependencies
# From repository root
pip3 install -r mcp/requirements.txt
pip3 install requests beautifulsoup4
2. Quick Setup (Automated)
# Run the setup script
./setup_mcp.sh
# Follow the prompts - it will:
# - Install dependencies
# - Test the server
# - Generate configuration
# - Guide you through Claude Code setup
3. Manual Setup
Add to ~/.config/claude-code/mcp.json:
{
"mcpServers": {
"skill-seeker": {
"command": "python3",
"args": [
"/path/to/Skill_Seekers/mcp/server.py"
],
"cwd": "/path/to/Skill_Seekers"
}
}
}
Replace /path/to/Skill_Seekers with your actual repository path!
4. Restart Claude Code
Quit and reopen Claude Code (don't just close the window).
5. Test
In Claude Code, type:
List all available configs
You should see a list of preset configurations (Godot, React, Vue, etc.).
Available Tools
The MCP server exposes 6 tools:
1. generate_config
Create a new configuration file for any documentation website.
Parameters:
name(required): Skill name (e.g., "tailwind")url(required): Documentation URL (e.g., "https://tailwindcss.com/docs")description(required): When to use this skillmax_pages(optional): Maximum pages to scrape (default: 100)rate_limit(optional): Delay between requests in seconds (default: 0.5)
Example:
Generate config for Tailwind CSS at https://tailwindcss.com/docs
2. estimate_pages
Estimate how many pages will be scraped from a config (fast, no data downloaded).
Parameters:
config_path(required): Path to config file (e.g., "configs/react.json")max_discovery(optional): Maximum pages to discover (default: 1000)
Example:
Estimate pages for configs/react.json
3. scrape_docs
Scrape documentation and build Claude skill.
Parameters:
config_path(required): Path to config fileenhance_local(optional): Open terminal for local enhancement (default: false)skip_scrape(optional): Use cached data (default: false)dry_run(optional): Preview without saving (default: false)
Example:
Scrape docs using configs/react.json
4. package_skill
Package a skill directory into a .zip file ready for Claude upload.
Parameters:
skill_dir(required): Path to skill directory (e.g., "output/react/")
Example:
Package skill at output/react/
5. list_configs
List all available preset configurations.
Parameters: None
Example:
List all available configs
6. validate_config
Validate a config file for errors.
Parameters:
config_path(required): Path to config file
Example:
Validate configs/godot.json
Example Workflows
Generate a New Skill from Scratch
User: Generate config for Svelte at https://svelte.dev/docs
Claude: ✅ Config created: configs/svelte.json
User: Estimate pages for configs/svelte.json
Claude: 📊 Estimated pages: 150
User: Scrape docs using configs/svelte.json
Claude: ✅ Skill created at output/svelte/
User: Package skill at output/svelte/
Claude: ✅ Created: output/svelte.zip
Ready to upload to Claude!
Use Existing Preset
User: List all available configs
Claude: [Shows all configs: godot, react, vue, django, fastapi, etc.]
User: Scrape docs using configs/react.json
Claude: ✅ Skill created at output/react/
User: Package skill at output/react/
Claude: ✅ Created: output/react.zip
Validate Before Scraping
User: Validate configs/godot.json
Claude: ✅ Config is valid!
Name: godot
Base URL: https://docs.godotengine.org/en/stable/
Max pages: 500
Rate limit: 0.5s
User: Scrape docs using configs/godot.json
Claude: [Starts scraping...]
Architecture
Server Structure
mcp/
├── server.py # Main MCP server
├── requirements.txt # MCP dependencies
└── README.md # This file
How It Works
- Claude Code sends MCP requests to the server
- Server routes requests to appropriate tool functions
- Tools call CLI scripts (
doc_scraper.py,estimate_pages.py, etc.) - CLI scripts perform actual work (scraping, packaging, etc.)
- Results returned to Claude Code via MCP protocol
Tool Implementation
Each tool is implemented as an async function:
async def generate_config_tool(args: dict) -> list[TextContent]:
"""Generate a config file"""
# Create config JSON
# Save to configs/
# Return success message
Tools use subprocess.run() to call CLI scripts:
result = subprocess.run([
sys.executable,
str(CLI_DIR / "doc_scraper.py"),
"--config", config_path
], capture_output=True, text=True)
Testing
The MCP server has comprehensive test coverage:
# Run MCP server tests (25 tests)
python3 -m pytest tests/test_mcp_server.py -v
# Expected output: 25 passed in ~0.3s
Test Coverage
- Server initialization (2 tests)
- Tool listing (2 tests)
- generate_config (3 tests)
- estimate_pages (3 tests)
- scrape_docs (4 tests)
- package_skill (2 tests)
- list_configs (3 tests)
- validate_config (3 tests)
- Tool routing (2 tests)
- Integration (1 test)
Total: 25 tests | Pass rate: 100%
Troubleshooting
MCP Server Not Loading
Symptoms:
- Tools don't appear in Claude Code
- No response to skill-seeker commands
Solutions:
-
Check configuration:
cat ~/.config/claude-code/mcp.json -
Verify server can start:
python3 mcp/server.py # Should start without errors (Ctrl+C to exit) -
Check dependencies:
pip3 install -r mcp/requirements.txt -
Completely restart Claude Code (quit and reopen)
-
Check Claude Code logs:
- macOS:
~/Library/Logs/Claude Code/ - Linux:
~/.config/claude-code/logs/
- macOS:
"ModuleNotFoundError: No module named 'mcp'"
pip3 install -r mcp/requirements.txt
Tools Appear But Don't Work
Solutions:
-
Verify
cwdin config points to repository root -
Check CLI tools exist:
ls cli/doc_scraper.py ls cli/estimate_pages.py ls cli/package_skill.py -
Test CLI tools directly:
python3 cli/doc_scraper.py --help
Slow Operations
- Check rate limit in configs (increase if needed)
- Use smaller
max_pagesfor testing - Use
skip_scrapeto avoid re-downloading data
Advanced Configuration
Using Virtual Environment
# Create venv
python3 -m venv venv
source venv/bin/activate
pip install -r mcp/requirements.txt
pip install requests beautifulsoup4
which python3 # Copy this path
Configure Claude Code to use venv Python:
{
"mcpServers": {
"skill-seeker": {
"command": "/path/to/Skill_Seekers/venv/bin/python3",
"args": ["/path/to/Skill_Seekers/mcp/server.py"],
"cwd": "/path/to/Skill_Seekers"
}
}
}
Debug Mode
Enable verbose logging:
{
"mcpServers": {
"skill-seeker": {
"command": "python3",
"args": ["-u", "/path/to/Skill_Seekers/mcp/server.py"],
"cwd": "/path/to/Skill_Seekers",
"env": {
"DEBUG": "1"
}
}
}
}
With API Enhancement
For API-based enhancement (requires Anthropic API key):
{
"mcpServers": {
"skill-seeker": {
"command": "python3",
"args": ["/path/to/Skill_Seekers/mcp/server.py"],
"cwd": "/path/to/Skill_Seekers",
"env": {
"ANTHROPIC_API_KEY": "sk-ant-your-key-here"
}
}
}
}
Performance
| Operation | Time | Notes |
|---|---|---|
| List configs | <1s | Instant |
| Generate config | <1s | Creates JSON file |
| Validate config | <1s | Quick validation |
| Estimate pages | 1-2min | Fast, no data download |
| Scrape docs | 15-45min | First time only |
| Scrape (cached) | <1min | With skip_scrape |
| Package skill | 5-10s | Creates .zip |
Documentation
- Full Setup Guide: docs/MCP_SETUP.md
- Main README: README.md
- Usage Guide: docs/USAGE.md
- Testing Guide: docs/TESTING.md
Support
- Issues: GitHub Issues
- Discussions: GitHub Discussions
License
MIT License - See LICENSE for details