"Integrating Tavily with IDE" matching MCP servers:

MCP server for web page fetching (converting to Markdown/text with automatic fallback between Tavily and Firecrawl) and web search via Tavily.

A basic MCP server built with the FastMCP framework that provides fundamental mathematical operations like addition, subtraction, multiplication, and division. It serves as a demonstration for integrating math-based tools into MCP-compatible environments like Cursor IDE.

A typed FastMCP server that wraps Tavily's web research API, providing tools for search, extract, map, crawl, and research workflows via MCP with prompts and resources.

A Model Context Protocol server for web scraping and searching, with automatic fallback from Tavily to Firecrawl for fetching web content.

Enables AI agents to perform real-time web searches and extract clean, LLM-readable content from URLs using the Tavily API.

An MCP server that enables LLMs to automate browser interactions using Playwright to fetch real-time Israeli weather data.

Enables MCP clients to perform Tavily-compatible search and extract operations against a self-hosted TrailSearch/open-tavily API by using a custom base URL instead of the default Tavily endpoint.

MCP server that provides web search capabilities using the Tavily API.

Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.

A minimal MCP server that exposes a run_command tool over stdio, enabling command execution within a Docker container.

Provides advanced web search, content extraction, site crawling, mapping, and AI-powered research capabilities through the Tavily API with automatic multi-key fallback for rate limiting.

Enables web search via Tavily API and URL shortening with custom aliases and fallback services.

Provides AI assistants with progressive code intelligence to explore repository structure, find symbols, and assess the impact of changes using ast-grep.

Hands local video files to Gemini's native video understanding for detailed, timestamped descriptions, and also supports image/media viewing with frame extraction.

A read-only DuckDB MCP server offering context-efficient analytics tools (list_datasets, describe_table, profile_column, explain, query) with a semantic layer for business rules, security guards, and disclosed truncation to help LLMs produce correct answers while minimizing token usage.

Enables users to ask natural-language questions about a local folder's contents, including file names, sizes, and timestamps, with rollups by type and age and cleanup suggestions for stale or large files. It returns metadata only and cannot read, move, or delete files.

Read-only SQL MCP server for quantitative finance data (DuckDB) with stock quotes, financials, and historical K-lines, enabling cross-database JOIN queries.

Enables real-time domain registration lookups via RDAP, including availability, expiration, and registrar details, with no API key required. Supports natural language queries like 'is example.com available?' or 'when does example.com expire?'.

Enables AI agents to drive the 1C:Enterprise test client directly, opening forms, reading and modifying data, working with tables, and recording or replaying action scenarios. Connects to local or remote test clients over their network protocol without a testing manager.

Enables AI agents to query US public company financial data from SEC filings, with tools for resolving tickers, listing filings, retrieving financial concepts, comparing companies, extracting filing sections, and full-text search. It surfaces data ambiguities like tag variations, restatements, and fiscal-year misalignment rather than hiding them.