"Connecting to Gemini Flash Experimental" matching MCP servers:

MCP server for AI-powered research using Gemini. Provides fast grounded web search, deep autonomous research, URL extraction, and session management.

Integrates Gemini API research capabilities (Deep Research, Quick Search, URL Analysis) into a unified MCP server, enabling comprehensive research, web search, and URL analysis through natural language.

A Model Context Protocol server leveraging Google's Gemini Flash 2 to analyze datasets, generate research papers, and deliver results via email.

Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.

An MCP server that enables advanced CSV analysis and data visualization using Google's Gemini AI and Plotly. It allows users to perform exploratory data analysis, generate interactive charts, and conduct complex reasoning on tabular data.

Converts PDF files to text for use with MCP-compatible applications like Cursor IDE.

Provides web and local search capabilities via Brave Search combined with advanced academic paper analysis using Google's Gemini model. It allows AI assistants to perform real-time information retrieval and structured research synthesis directly through the Model Context Protocol.

An MCP server implementation that leverages Google's Gemini API to provide analytical problem-solving capabilities through sequential thinking steps without code generation.

This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.

Enables AI assistants to programmatically access and manage Gemini Notebook (formerly Google NotebookLM), including creating notebooks, adding sources, querying content, generating studio content, downloading artifacts, and running batch or cross-notebook workflows through natural language.

Enables AI assistants to programmatically interact with Google NotebookLM, allowing them to create and manage notebooks, add sources, query content, generate audio/video, and perform research tasks through natural language commands.

Enables Claude Code to convert PDF files to high-quality PNG images, download academic papers, and batch process PDFs with automatic folder organization.

Converts Digital Object Identifiers (DOIs) to BibTeX format using the official DOI content negotiation API, enabling users to quickly generate bibliography entries for academic papers.

Enables searching and retrieving UK research grants, award values, institutions, and publications from the UKRI Gateway to Research API without authentication.

Enables keyword analysis and search volume data through the Marketing Miner API, connecting marketing intelligence tools to AI assistants like Cursor, Claude, and Windsurf.

Enables offline local LLM analysis of text data via MCP, taking raw text and an instruction to return analysis results without cloud calls.

MCP server connecting AI models to Swiss Federal Food Safety and Veterinary Office open data, enabling queries about food recalls, animal disease surveillance, food control results, and more.

Enables AI agents to read and analyze PDF documents for natural language Q\&A. Supports multiple LLM providers including Google Gemini, Anthropic Claude, and OpenAI.

Wraps a hosted prediction market API to expose estimation, sizing, scanning, ensemble, and service-information tools for experimental research, returning payment-required details on HTTP 402 responses without handling payment itself.

Connects to wetlab protocol resources such as protocols.io, enabling users to access and manage experimental protocols via natural language.