xpay✦ Marketing Collection

tavily_search

Search the web for current information on any topic. Use for news, facts, or data beyond your knowledge cutoff. Returns snippets and source URLs.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`query`	Yes	Search query
`topic`	No	The category of the search. This will determine which of our agents will be used for the search	general
`country`	No	Boost search results from a specific country. Must be a full country name (e.g., 'United States', 'Japan', 'Germany'). ISO country codes (e.g., 'us', 'jp') are not supported. Available only if topic is general. See https://docs.tavily.com/documentation/api-reference/search for the full list of supported countries.
`end_date`	No	Will return all results before the specified end date. Required to be written in the format YYYY-MM-DD
`start_date`	No	Will return all results after the specified start date. Required to be written in the format YYYY-MM-DD.
`time_range`	No	The time range back from the current date to include in the search results
`exact_match`	No	Only return results containing the exact phrase(s) in quotes in your query
`max_results`	No	The maximum number of search results to return
`search_depth`	No	The depth of the search. 'basic' for generic results, 'advanced' for more thorough search, 'fast' for optimized low latency with high relevance, 'ultra-fast' for prioritizing latency above all else	basic
`include_images`	No	Include a list of query-related images in the response
`exclude_domains`	No	List of domains to specifically exclude, if the user asks to exclude a domain set this to the domain of the site
`include_domains`	No	A list of domains to specifically include in the search results, if the user asks to search on specific sites set this to the domain of the site
`include_favicon`	No	Whether to include the favicon URL for each result
`include_raw_content`	No	Include the cleaned and parsed HTML content of each search result
`include_image_descriptions`	No	Include a list of query-related images and their descriptions in the response

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed3 schema fields changedApr 19, 2026

addedInput schema / additionalProperties
```
Added value: +false
```

changedInput schema / properties / country / description

Previous value: -"Boost search results from a specific country. This will prioritize content from the selected country in the search results. Available only if topic is general."New value: +"Boost search results from a specific country. Must be a full country name (e.g., 'United States', 'Japan', 'Germany'). ISO country codes (e.g., 'us', 'jp') are not supported. Available only if topic is general. See https://docs.tavily.com/documentation/api-reference/search for the full list of supported countries."

addedInput schema / properties / exact_match

Added value: +{
+  "anyOf": [
+    {
+      "type": "boolean"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Only return results containing the exact phrase(s) in quotes in your query"
+}

First observedMar 14, 2026

TDQS

A3.7/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full disclosure burden. It does reveal the output format ('snippets and source URLs') and implies a non-destructive read operation, but it does not mention authentication requirements, rate limits, or any caveats about result freshness or accuracy. This is a moderate disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences, front-loaded with the primary action, and every phrase contributes value. It is concise without being under-specified.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 15 parameters and no output schema, the description is minimal but covers the main purpose and basic return type. However, it does not explain the richer response fields that parameters like include_images or include_raw_content imply, nor does it guide selection among sibling search tools, leaving some gaps for complex use cases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already provides descriptions for all 15 parameters (100% coverage), so the description need not elaborate on individual parameters. It adds no extra parameter semantics beyond saying the tool searches the web, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it searches the web for current information, with a specific verb and resource. It also mentions typical use cases (news, facts, data beyond knowledge cutoff). However, it does not explicitly distinguish itself from sibling search tools like tavily_research or web_search_exa, so it is not a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use it: for news, facts, or data beyond the knowledge cutoff. It does not, however, mention when not to use it or point to alternative tools for different scenarios, missing the higher tier.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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