Retrieve Tavily API usage and quota information. Automatically rotates multiple API keys to prevent rate limiting.
MIT
260,585 tools. Last updated 2026-07-05 07:35
"Information or meaning related to 'Tavily'" matching MCP tools:
- Search the web for information using multiple providers (Tavily, Brave, Kagi) with support for query operators and domain filtering.MIT
- Search the web using Tavily to obtain current information. Returns structured results suitable for financial analysis.MIT
- Search the web using configured engines like Exa, Tavily, DuckDuckGo, or direct HTTP fallback for information retrieval.Business Source 1.1
- Search the web for information using natural language queries through the Tavily API. This tool retrieves search results to answer questions and provide context.
- Search the web for real-time information using the Tavily API to answer queries and gather current data.
Matching MCP Servers
- Alicense-qualityAmaintenanceEnables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.Last updated221MIT
Tavily MCP Serverofficial
AlicenseAqualityDmaintenanceThis server enables AI systems to integrate with Tavily's search and data extraction tools, providing real-time web information access and domain-specific searches.Last updated428,2992,146MIT
Matching MCP Connectors
Tavily MCP — wraps the Tavily API (tavily.com)
Transform any blog post or article URL into ready-to-post social media content for Twitter/X threads, LinkedIn posts, Instagram captions, Facebook posts, and email newsletters. Pay-per-event: $0.07 for all 5 platforms, $0.03 for single platform.
- Extract content from any URL using the Tavily API to retrieve web page information for analysis or processing.
- Search code by name, content, or meaning with literal matching and path globs. Optionally list all matching files exhaustively.MIT
- Search conversation memory by meaning to recall prior context across sessions, such as past decisions or agreements.MIT
- Find entities in the knowledge graph by meaning rather than exact text matching, enabling retrieval of related concepts even without keyword overlap.MIT
- Search indexed datasets by keyword or meaning to find specific documents without reprocessing files. Supports structured, semantic, and hybrid modes with optional filters.MIT
- Search agent memories by semantic meaning to find relevant information before starting tasks when exact keypaths are unknown.Apache 2.0
- Retrieve stored information from long-term memory using semantic meaning, keywords, or both to provide context about topics when users ask questions.MIT
- Find passages by meaning rather than exact words across your Scrivener project. Use conceptual queries to locate relevant documents with similarity scores and related entities.AGPL 3.0
- Search documents using semantic understanding to find relevant content based on meaning rather than keywords. Understands natural language queries and returns ranked passages with source information.MIT
- Create relationships between existing memory entities by specifying a subject, verb, and object to connect related information.MIT
- Find coins related to a given coin by category or sector similarity. Provide the canonical coin ID to retrieve a list of related coins, optionally limiting the number.MIT
- Search medical concepts with natural language neural embeddings. Understands clinical meaning, mapping everyday terms to standard codes across SNOMED, ICD-10, RxNorm, LOINC.MIT
- Extracts clean plain text from a URL using Tavily. Returns readable content for analysis, avoiding binary or structured data.Apache 2.0
- Find medical concepts similar to a reference concept, name, or query using semantic, lexical, or hybrid algorithms. Explore related concepts and build phenotype sets.MIT