"Extracting and Processing Real Estate Listings Using Vector Databases" matching MCP servers:

Enables querying Taiwan real-estate actual-price transaction data through MCP tools, including transaction search, market statistics, area listing, and data status, using a local SQLite database.

An MCP server that enables AI assistants to create and run Processing sketches directly through natural language commands.

Turn real-estate listing photos into cinematic property videos from your AI assistant. reel-estate-mcp is a Model Context Protocol (MCP) server that connects Claude, Cursor, and other AI assistants to your Reel Estate account — so you can generate motion clips, AI-edit photos (virtual staging, twilight, seasonal), add voiceover, and render finished listing videos, all in plain language.

A deterministic SVG perception tool for LLM agents that renders SVGs in a real browser to measure geometry, colors, and spatial constraints, reporting results in grid grammar and W3C color names without guessing.

A secure vector-based memory server that provides persistent semantic memory for AI assistants using sqlite-vec and sentence-transformers. It enables semantic search and organization of coding experiences, solutions, and knowledge with features like auto-cleanup and deduplication.

Enables image processing tasks such as resizing, compressing, converting formats, cropping, and extracting metadata directly within IDEs like Cursor via the Model Context Protocol.

Enables semantic and full-text search over markdown notes, with tools to create, edit, move, and delete notes, all through MCP. Runs entirely locally using Ollama for embeddings and SQLite for storage, working with Obsidian or standalone.

Enables local vector database operations with a Pinecone-compatible API, supporting exact and approximate search, metadata filtering, and semantic text queries over MCP.

Enables agents to turn documents into vectors, perform approximate nearest neighbor search with HNSW, and filter by metadata via MCP tools for RAG workflows.

Enables fetching weather forecasts for the USA via NWS API and for Israel via browser automation using Playwright.

Enables automated collection of apartment listing data from Naver Real Estate using Playwright browser automation with passive network response capture. Provides MCP tools to search complexes, resolve property identifiers, and extract normalized listing information including duplicate properties.

Enables semantic code search over a local codebase using Qdrant vector embeddings and OpenAI embeddings, allowing natural language queries from MCP-compatible clients like Claude Desktop.

MCP server + Chrome extension that gives AI coding agents control of your real browser with existing sessions, logins, and cookies. Works with Cursor, Claude, Windsurf.

Enables browser automation over MCP using a real Chrome browser with existing profile, supporting real tabs, downloads, cookies, and RPA workflows.

Enables indexing and semantic search of software project files via MCP, with automatic file watching for updates.

Provides local vector-based semantic memory storage for AI assistants to persist context and decisions across sessions using local embeddings and LanceDB. It enables private semantic search and session handoff capabilities to maintain long-term project context.

A secure, vector-based task management server for Claude Desktop using sqlite-vec and sentence-transformers. It provides intelligent task tracking with semantic search capabilities to organize and retrieve development tasks efficiently.

Lets any LLM agent actually watch videos: a watch_video tool takes a URL or local file and returns scene-aware keyframes fused with a timestamped transcript, processed 100% locally with per-source caching.

Enables real-time web page fetching, web searches, RSS/Atom feed parsing, and competitor mention tracking to monitor market and competitor changes.

Enables AI assistants to save and recall information from files or free-form notes using natural language, acting as a long-term memory system.