"Automating document interaction, download, and conversion for AI-driven answers" matching MCP servers:

A local document evidence layer for MCP clients that ingests documents (PDF, Office, images) with optional OCR, indexes them in SQLite FTS, and provides retrieval tools with source coordinates.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

Search the fastest-growing US horse boarding directory: 6,000 facilities and 3,800 trainers across 48 states, plus boarding price data by state.

Enables a unified AI assistant that combines document retrieval (RAG), database queries via MCP tools, and web search, allowing users to ask complex questions and receive answers from multiple enterprise sources.

Enables chat, document search (RAG), and a declarative SQL tool builder over MCP so any client can use these capabilities.

A server that enables document searching using Vertex AI with Gemini grounding, improving search results by grounding responses in private data stored in Vertex AI Datastore.

Enables governed interaction with synthetic people data through MCP tools, providing per-caller scoped access, semantic-layer metrics, and read-only SQL with authorization checks.

MCP server that connects AI assistants to Redash, enabling listing of assets, read-only query execution, dashboard inspection, and alert management through the Redash API.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

Enables natural language interaction with heterogeneous databases (MySQL and PostgreSQL) for CRUD operations across customer, product, and sales data with intelligent query routing and visualization capabilities.

Universal database copilot for diagnostics, operations, and performance analysis via MCP and CLI.

MCP server enabling text-to-SQL on PostgreSQL databases using a CrewAI multi-agent system. It generates and executes read-only SQL queries from natural language, with security layers against prompt injection.

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

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.

Enables AI agents to conversationally interact with genomics research networks for data analysis and discovery across multiple Omics AI Explorer platforms. It provides tools for exploring data collections, examining table schemas, and executing SQL queries against datasets like Viral AI and Neuroscience AI.

MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.

Enables AI assistants to use Neo4j knowledge graphs and Qdrant vector databases for hybrid reasoning, combining structured facts with semantic search for advanced knowledge management, research analysis, and standardized coding workflows.

A Model Context Protocol (MCP) server for developing Django applications. It exposes Django project information through MCP tools, enabling AI assistants to better understand and interact with Django codebases.

Enables users to ask natural-language questions about live 1C:Enterprise data and receive answers from read-only OData sources, covering sales, inventory, items, and counterparties; supports direct connections or an SSH tunnel for IP-allowlisted installations.

Enables AI clients to securely access and query Microsoft Dynamics 365 data through natural language, supporting data analysis, reporting, and business workflows.