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

Enables AI agents to semantically search GitHub repository documentation by automatically fetching, vectorizing, and indexing content into an Upstash Vector database. It provides a standard MCP interface for agents to retrieve relevant documentation snippets through natural language queries.

Enables conversion of PDF files to Markdown format with optional image extraction using docling. Supports batch processing of multiple PDFs with structured output including metadata and processing statistics.

Enables AI clients to search live documentation for popular developer libraries and return clean, source-cited summaries via a RAG pipeline.

Enables AI assistants to search and retrieve documentation, component specs, theme guides, and CLI commands for the Meta Astryx Design System, providing structured tools and guidelines for coding agents.

Extracts and stores documentation content from Microsoft Learn and GitHub URLs into PocketBase with full-text search, metadata preservation, and automatic collection management for easy retrieval and organization.

MCP server that enables AI assistants to drive systematic literature review workflows, including screening, downloading, converting, and reviewing papers through natural language conversation.

A collection of MCP servers for Slack, Jira, Confluence, and release coordination to automate QA workflows and daily release status reporting.

Provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.

Enables PDF processing and analysis including text extraction, metadata retrieval, search, page manipulation, splitting/merging, conversion to images, and form handling.

Allows AI assistants to fetch and read Enterprise WeChat documents in real time using cookie authentication and HTML-to-Markdown conversion.

Converts PDF files from local storage or URLs to structured Markdown format using Mistral AI's OCR API, preserving document structure and extracting images.

A PDF MCP server for extracting text, rendered pages, tables, links, annotations, outlines, metadata, and text statistics from PDF files.

Assists in writing academic papers by extracting, organizing, and referencing scientific PDFs with ABNT formatting.

Enables AI assistants to parse and convert PDFs and images to structured text formats using the Doc2x v2 API. Supports asynchronous document processing, format conversion, and file downloads with configurable polling and timeout settings.

Enables document processing through Upstage AI services including parsing various document formats, extracting structured information with custom schemas, auto-generating extraction schemas, and classifying documents into categories.

Enables document parsing and extraction from PDFs and other formats using the MinerU API. Supports batch processing, page range selection, OCR in 109 languages, and VLM/pipeline models for high-accuracy content extraction.

A Model Context Protocol server that converts over 29 file formats, including PDFs, Office documents, and audio, into structured Markdown using Microsoft's MarkItDown library. It enables AI assistants to process diverse document types through single file conversion and batch directory processing.

Enables semantic search over local markdown documentation by indexing files and ranking results using vector similarity and BM25 fusion.

Provides LLMs with secure, read-only access to local documentation by scanning directories, extracting content from PDF, DOCX, Markdown, and text files, and performing keyword searches.

An offline-first MCP server for querying Google ADK documentation using vector search, enabling AI models to access and understand ADK docs.