"A server for finding information about text analytics" matching MCP servers:

Read-only MCP server providing curated SAP analytics market data, including firms, opportunities, news, concepts, and day-rate benchmarks, with citations and public tools requiring no credentials.

OrionBelt Analytics is an MCP server that analyzes relational database schemas and generates RDF/OWL ontologies with embedded SQL mappings. It provides relationship-aware Text-to-SQL with automatic fan-trap prevention, GraphRAG for intelligent schema discovery, and interactive charting -- all accessible through any MCP-compatible AI client.

An MCP server that combines SQL and RAG tools into a reasoning agent for answering retail analytics questions using natural language.

Enables agents to answer analytics questions with provable correctness by resolving metrics through the semantic layer, tracing lineage, traversing knowledge graphs, checking freshness, and searching glossary definitions, while enforcing access controls and logging every call.

A FastMCP-powered server that connects Google Analytics 4 data to Claude Desktop with automatic OAuth 2.0 authentication, enabling users to access GA4 metrics, properties, and reports through natural language queries.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Translates plain English questions about infrastructure operations into SQL queries, executes them against a database, and returns the real answer.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

An MCP server that implements Retrieval-Augmented Generation to efficiently retrieve and process important information from various sources, providing accurate and contextually relevant responses.

A Multi-Agent Conversation Protocol server that enables users to interact with the Redeal.io analytics API through natural language, automatically generated using AG2's MCP builder.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

A proof of concept MCP server for Apache OFBiz

This read-only MCP Server allows you to connect to YouTube Analytics data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp

Natural Language Analytics MCP server for Apache Druid. With this enterprise ready server in Java, one can query Apache Druid by natural language queries. Furthermore, the complete management like data loading of the Time Series Database Druid can be done with natural language commands.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Enables asking questions and performing semantic searches against an Inkeep knowledge base. Deployable to Vercel with Next.js.

Enables querying live Zora token data and analytics methodology through SQL and document retrieval tools, providing guarded access to on-chain holder, transfer, and token information.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for eBay Analytics (beta): https://www.cdata.com/download/download.aspx?sku=JJZK-V&type=beta

Turns any static website into an MCP-searchable knowledge base by deploying a Cloudflare Worker that provides full-text search tools, enabling AI assistants to search and retrieve content from your site.

An MCP server that extracts clean, structured Markdown content from web page URLs using the WebforAI library. It simplifies feeding web content into AI models by removing HTML noise and intelligently processing tables and links.