tavily-search-mcp-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| TRANSPORT | No | Transport mechanism to use (set to 'sse' for SSE transport) | |
| TAVILY_API_KEY | Yes | Your Tavily API key obtained from the Tavily dashboard |
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 | Performs a web search using the Tavily Search API, optimized for LLMs. Use this for broad information gathering, recent events, or when you need diverse web sources. Supports search depth, topic selection, time range filtering, and domain inclusion/exclusion. |
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 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'tavily_search' has a clear, distinct purpose focused on web search functionality.
A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'tavily_search' follows a clear and descriptive pattern.
One tool is too few for a server with a broad purpose like web search, as it lacks complementary operations such as filtering results, managing search history, or handling different search types. This minimal scope limits agent workflows and feels incomplete.
The tool surface is severely incomplete for a web search domain; it only provides a basic search function without supporting operations like refining searches, saving results, or accessing search metadata. This creates significant gaps that will hinder agent effectiveness.