Tavily MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| TAVILY_API_KEY | Yes | Your Tavily API key (required). You can get one at https://app.tavily.com/home |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| tavily-searchA | A powerful web search tool that provides comprehensive, real-time results using Tavily's AI search engine. Returns relevant web content with customizable parameters for result count, content type, and domain filtering. Ideal for gathering current information, news, and detailed web content analysis. |
| tavily-extractC | A powerful web content extraction tool that retrieves and processes raw content from specified URLs, ideal for data collection, content analysis, and research tasks. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: tavily-extract is for extracting content from specific URLs, while tavily-search is for performing web searches with customizable parameters. There is no overlap or ambiguity, making it easy for an agent to select the appropriate tool based on the task.
Both tools follow a consistent naming pattern with the prefix 'tavily-' followed by a descriptive action (extract, search). This uniformity makes the tool set predictable and easy to understand, with no deviations in style or convention.
With only two tools, the server feels under-scoped for a web content and search domain. While the tools cover extraction and search, the lack of additional operations (e.g., summarization, filtering, or advanced analysis) limits functionality and may require agents to work around gaps, making the set feel incomplete for broader use cases.
The tools cover basic web content retrieval (extract and search), but there are notable gaps in the surface. For example, there are no tools for processing or analyzing the extracted content (e.g., summarization, translation, or sentiment analysis), which could hinder agents in performing comprehensive tasks beyond raw data collection.