"Using LLMs for Retrieving and Processing Web Content" matching MCP servers:

Enables AI models to interact with IBM FileNet Content Manager for document management, folder operations, metadata handling, search, and content extraction through a standardized interface.

A Model Context Protocol server that enables LLMs to interact directly with MongoDB databases, allowing users to query collections, inspect schemas, and manage data through natural language.

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

An MCP server that enables large language models to interact directly with MongoDB databases, allowing them to query collections, inspect schemas, and manage data through natural language.

A Model Context Protocol server that enables large language models to interact directly with Couchbase databases through natural language, supporting operations like querying buckets, performing CRUD operations, and executing N1QL queries.

A Model Context Protocol server that enables LLMs to interact directly with MongoDB databases, allowing users to query collections, inspect schemas, and manage data through natural language.

Stores Organizations content

Enables Directus users to interact with their data in LLMs, allowing content editors and data analysts to manage content, query collections, and perform data operations using natural language.

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.

Processes emails from Outlook with date filtering, storing them in SQLite databases while generating vector embeddings for semantic search capabilities in MongoDB.

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.

A Machine Control Protocol (MCP) server that enables storing and retrieving information from a Qdrant vector database with semantic search capabilities.

An MCP server that gives LLM clients access to a SQL Server database and the local filesystem, including file operations and image handling.

A FastMCP-based server designed for the banking and fintech domains, providing tools for database queries, Git operations, and deployment management. It features a modular architecture with reusable prompt templates and integrated security practices for sensitive data handling.

Enables LLMs to extract content from websites using automated static and dynamic scraping engines with built-in anti-bot protections. It provides tools for web data retrieval and stores results in MongoDB with support for JSON and CSV exports.

MCP server demonstrating elicitation for booking appointments and an interactive MCP App for viewing appointments with SQLite persistence.

Enables AI applications to run SQL queries and retrieve results from Oracle Database.

Enables secure access to Oracle databases with fine-grained access control, supporting multiple databases simultaneously with configurable access modes (readonly/readwrite/full) and table-level permissions for safe query execution and data management.