"A server for searching research papers, Kaggle datasets, and websites for ML/AI model training data" matching MCP servers:

Enables real-time tracking of AI/LLM research progress by searching and aggregating content from arXiv, GitHub, Hugging Face, and Papers with Code. Supports intelligent search, automated daily/weekly research summaries, and covers 15+ AI research areas with smart caching.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

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

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

Enables semantic search across scientific papers in your Zotero library with hybrid search, incremental indexing, and cross-encoder reranking.

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.

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.

Enables AI coding agents to run Tavily-powered web searches and asynchronous, cited research through MCP, with tools for focused search, task creation, and status retrieval.

Enables AI assistants to perform comprehensive research by searching Google, mining Reddit discussions, scraping web content with JS rendering, and synthesizing findings with citations into structured context.

A Python-based agent that integrates research providers (OpenAI, Gemini, DR-Tulu, Open Deep Research) with Claude Code via the Model Context Protocol for automated deep research.

A deep-research MCP server exposing a single task-augmented tool that runs GPT-Researcher with Tavily search, Anthropic Claude, and OpenAI embeddings, streaming progress via MCP tasks and Upjack entity stream.

MCP server that searches 9 sources, scrapes full content, reranks results, and synthesizes cited answers with free LLMs.

A TypeScript-based server to interact with ArangoDB using the Model Context Protocol, enabling database operations and integration with tools like Claude and VSCode extensions for streamlined data management.

Enables source-grounded prior-art and novelty research by searching patents, publications, and the web in one run, verifying evidence levels, and returning a structured report.

Provides structured web search capabilities optimized for technical and software development content via providers like OpenRouter. It enables AI agents to perform research and retrieve relevant technical data in a consistent, programmatic JSON format.

An MCP server that retrieves and provides AI model information from OpenAI, Anthropic, and Google through a unified interface.

A Model Context Protocol compliant server that facilitates comprehensive web research by utilizing Tavily's Search and Crawl APIs to gather and structure data for high-quality markdown document creation.

Enables iterative deep research by integrating AI agents with search engines, web scraping, and large language models for efficient data gathering and comprehensive reporting.

MCP server that answers questions using Reddit discussions as evidence, searching threads, fetching comments, and ranking useful context, with optional cited answer synthesis.