Documentation for specific tools and integrations in IPFS Datasets Python.
The MCP (Model Context Protocol) server provides 200+ tools across 49+ categories:
- MCP Server Integration - Main MCP server guide
- MCP Dashboard - MCP dashboard
- Municipal Codes Tool Guide - Municipal code scraping
- Municipal Codes Dashboard - Dashboard interface
- Patent Scraper Guide - Patent database scraping
- Web Search API Guide - Web search integration
- Brave Search Client - Brave Search API
- Brave Search IPFS Cache - Cached search results
- Common Crawl Integration - Common Crawl access
- Common Crawl Integration Summary - Integration overview
- FFmpeg Tools Integration - FFmpeg video/audio processing
- Media download from 1000+ platforms (YouTube, Vimeo, TikTok, etc.)
- CLI Error Auto-Healing - CLI error auto-fix
- JS Error Auto-Healing Guide - JavaScript error auto-fix
- Discord Alerts Guide - Discord integration
- CLI Caching Guide - CLI caching strategies
Most tools can be accessed via:
import anyio
from ipfs_datasets_py.mcp_server.tool_registry import ToolRegistry
async def main():
registry = ToolRegistry()
tool = await registry.get_tool("development", "github_cli_status")
result = await tool.execute({"install_dir": None})
print(result)
anyio.run(main)# Start MCP server
python -m ipfs_datasets_py.mcp_server
# Access via MCP protocol# Enhanced CLI with all tools
python scripts/cli/enhanced_cli.py --list-categories
python scripts/cli/enhanced_cli.py [category] [tool] [args]- dataset_tools - Dataset loading and processing
- embedding_tools - Vector embeddings
- search_tools - Search functionality
- pdf_tools - PDF processing
- media_tools - Multimedia processing
- legal_dataset_tools - Legal data scraping
- web_archive_tools - Web archiving
- vector_tools - Vector store operations
- ipfs_tools - IPFS operations
- ...and 40+ more categories
- MCP Tools Comprehensive Reference - Complete tool catalog
- MCP Tools Technical Reference - Technical details
- User Guide - General usage