About
HomeHarvest scrapes real estate property listings from multiple sources with advanced filtering capabilities for location, property type, date ranges, and more. Key features: - Extract comprehensive property details including pricing, specifications, and listing information - Filter searches by geographic location, property type, and listing date ranges - Generate comparable sales data (comps) for property valuation and market analysis - Support real estate investment research and lead generation workflows - Streamline data collection for market trend analysis and property research
README
homeharvest-mcp
An MCP server built with Smithery.
Remote MCP Server Setup @ smithery.ai
Prerequisites
Getting Started
1. Run the server:
uv run dev
2. Test interactively:
uv run playground
Try saying "Say hello to John" to test the example tool.
Development
Your server code is in src/hello_server/server.py. Add or update your server capabilities there.
Deploy
Ready to deploy? Push your code to GitHub and deploy to Smithery:
1. Create a new repository at github.com/new
2. Initialize git and push to GitHub:
git add .
git commit -m "Hello world 👋"
git remote add origin https://github.com/YOUR_USERNAME/YOUR_REPO.git
git push -u origin main
3. Deploy your server to Smithery at smithery.ai/new
Related MCP Servers
AI Research Assistant
hamid-vakilzadeh
AI Research Assistant provides comprehensive access to millions of academic papers through the Semantic Scholar and arXiv databases. This MCP server enables AI coding assistants to perform intelligent literature searches, citation network analysis, and paper content extraction without requiring an API key. Key features include: - Advanced paper search with multi-filter support by year ranges, citation thresholds, field of study, and publication type - Title matching with confidence scoring for finding specific papers - Batch operations supporting up to 500 papers per request - Citation analysis and network exploration for understanding research relationships - Full-text PDF extraction from arXiv and Wiley open-access content (Wiley TDM token required for institutional access) - Rate limits of 100 requests per 5 minutes with options to request higher limits through Semantic Scholar
Linkup
LinkupPlatform
Linkup is a real-time web search and content extraction service that enables AI assistants to search the web and retrieve information from trusted sources. It provides source-backed answers with citations, making it ideal for fact-checking, news gathering, and research tasks. Key features of Linkup: - Real-time web search using natural language queries to find current information, news, and data - Page fetching to extract and read content from any webpage URL - Search depth modes: Standard for direct-answer queries and Deep for complex research across multiple sources - Source-backed results with citations and context from relevant, trustworthy websites - JavaScript rendering support for accessing dynamic content on JavaScript-heavy pages
Math-MCP
EthanHenrickson
Math-MCP is a computation server that enables Large Language Models (LLMs) to perform accurate numerical calculations through the Model Context Protocol. It provides precise mathematical operations via a simple API to overcome LLM limitations in arithmetic and statistical reasoning. Key features of Math-MCP: - Basic arithmetic operations: addition, subtraction, multiplication, division, modulo, and bulk summation - Statistical analysis functions: mean, median, mode, minimum, and maximum calculations - Rounding utilities: floor, ceiling, and nearest integer rounding - Trigonometric functions: sine, cosine, tangent, and their inverses with degrees and radians conversion support