Tavily Web Search MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation2/5
The tools have unclear boundaries and overlapping purposes. 'load_bookmark_data' and 'organize_and_categorize' both deal with bookmark data, making it ambiguous which to use for basic operations. 'roll_dice' is completely unrelated to the web search/domain theme, creating confusion about the server's core purpose. An agent would struggle to differentiate when to use each tool appropriately.
Naming Consistency3/5
The naming conventions are mixed but still readable. 'load_bookmark_data' and 'web_search' follow a verb_noun pattern, while 'organize_and_categorize' uses a verb_and_verb style and 'roll_dice' is a simple verb_noun. There's no consistent pattern across all tools, but the names are descriptive enough to understand their functions individually.
Tool Count2/5
With only 4 tools, the count feels too thin for a 'Tavily Web Search MCP Server' as implied by the name. The inclusion of unrelated tools like 'roll_dice' and bookmark management functions suggests poor scoping. A focused web search server would typically have more search-related operations, making this set appear incomplete and mismatched to its stated purpose.
Completeness2/5
There are significant gaps in the tool surface for a web search domain. While 'web_search' exists, there's no support for advanced search features, result filtering, or search history management. The bookmark tools are incomplete without create/update/delete operations, and 'roll_dice' is entirely out of scope. This creates dead ends for agents trying to perform comprehensive web search tasks.
Average 3/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the action but doesn't disclose behavioral traits like whether rolls are random, if results are deterministic, error handling for invalid notation, or output format. This is a significant gap for a tool with parameters and an output schema.
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 a single, efficient sentence with no wasted words. It's front-loaded and appropriately sized for the tool's complexity, making it easy to parse quickly.
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 2 parameters with 0% schema coverage and an output schema, the description is incomplete. It hints at the 'notation' parameter but doesn't fully explain it or cover 'num_rolls'. The output schema likely handles return values, so that's not needed, but the description lacks sufficient detail for effective use without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions 'notation' but doesn't explain what dice notation entails (e.g., '2d6' for two six-sided dice). The 'num_rolls' parameter isn't addressed at all. The description adds minimal meaning beyond the schema, failing to compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Roll the dice with the given notation' states the action (roll) and resource (dice) but is vague about what 'notation' means. It doesn't differentiate from sibling tools like 'load_bookmark_data' or 'organize_and_categorize', but those are unrelated, so differentiation isn't needed. The purpose is understandable but lacks specificity about dice notation formats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention any context, prerequisites, or exclusions. Since sibling tools are unrelated (e.g., web_search), there's no explicit comparison, leaving usage unclear beyond the basic action.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool loads data but doesn't cover critical aspects like whether this is a read-only operation, potential side effects, error handling, or performance implications, which are essential for safe use.
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 a single, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded and appropriately sized for its purpose, earning a perfect score for conciseness.
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 an output schema (which handles return values) and only one parameter, the description is minimally adequate. However, with no annotations and low schema coverage, it lacks details on behavior and parameter usage, making it incomplete for fully informed use.
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 description mentions loading data 'from files', which loosely relates to the 'data_folder' parameter, but with 0% schema description coverage, it doesn't add meaningful details like supported file types or folder structure. Since there's only one parameter, the baseline is higher, but the description doesn't fully compensate for the lack of schema documentation.
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 the action ('Load') and the resource ('bookmarks and history data from files'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'organize_and_categorize' or 'web_search', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks context about prerequisites, such as file formats or locations, and doesn't mention any sibling tools for comparison, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions actions (clean, deduplicate, categorize) but doesn't specify whether this is a read-only or destructive operation, what permissions are needed, or any rate limits. This is a significant gap for a tool that implies data transformation.
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 a single, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for the tool's complexity, making it easy to parse and understand quickly.
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's moderate complexity (data processing with 2 parameters) and the presence of an output schema (which handles return values), the description is somewhat complete but lacks behavioral context. It covers the purpose but misses usage guidelines and transparency details, making it adequate but with clear gaps.
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 description adds no parameter semantics beyond what the input schema provides, as schema description coverage is 0% and the description doesn't mention parameters. However, with only 2 parameters and high schema coverage (titles and defaults are clear), the baseline is 3 since the schema handles the heavy lifting adequately.
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 the tool's purpose with specific verbs (clean, deduplicate, categorize) and resource (bookmark data), making it easy to understand what it does. However, it doesn't distinguish itself from sibling tools like 'load_bookmark_data' which might handle similar data, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'load_bookmark_data' for loading data or other siblings. It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage based on the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool searches the web but doesn't add context beyond that—such as rate limits, authentication needs, result format, or potential side effects. This is a significant gap for a tool that likely interacts with external resources.
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 a single, efficient sentence that front-loads the core action ('Search the web') and purpose. There is no wasted language, making it appropriately sized and easy to parse for an AI agent.
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's complexity (web search with external interaction), no annotations, and an output schema (which reduces need to explain return values), the description is minimally adequate. It covers the basic purpose but lacks behavioral context and usage guidelines, making it incomplete for optimal agent use.
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 input schema has 0% description coverage, so the description must compensate. It mentions 'the given query,' which aligns with the single parameter 'query,' adding some meaning. However, it doesn't provide details on query syntax, length limits, or examples, leaving gaps in parameter understanding.
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 the tool's purpose with a specific verb ('Search') and resource ('the web'), and it specifies the action is for information about a given query. However, it doesn't differentiate from sibling tools like 'organize_and_categorize' or 'load_bookmark_data', which might involve web-related functions, so it lacks sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any context, exclusions, or comparisons to sibling tools such as 'load_bookmark_data' for retrieving saved web data or 'organize_and_categorize' for processing web content, leaving the agent without usage direction.
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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