Tavily Web Search MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation1/5
The tools have wildly different and unrelated purposes—clipboard operations, dice rolling, email sending, and web searching—with no clear thematic connection, making the set highly ambiguous as a cohesive toolset. An agent would struggle to understand why these specific tools are grouped together, leading to potential misselection based on domain assumptions.
Naming Consistency4/5
The naming follows a consistent verb_noun pattern (e.g., read_clipboard, roll_dice, send_gmail, web_search, write_clipboard), which is predictable and readable. There are minor deviations like 'web_search' using a noun_verb structure instead, but overall the consistency is strong.
Tool Count2/5
With only 5 tools, the count is reasonable in isolation, but it is inappropriate for the server's stated purpose as 'Tavily Web Search MCP Server'—only one tool (web_search) directly relates to web searching, while the others are unrelated utilities, creating a mismatch in scope.
Completeness2/5
For a web search server, there are significant gaps in coverage, such as missing tools for advanced search features, result filtering, or API configuration. The inclusion of unrelated tools like clipboard and email operations further dilutes the domain focus, making the surface incomplete for the stated purpose.
Average 3.4/5 across 5 of 5 tools scored. Lowest: 2.7/5.
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 of behavioral disclosure. It mentions rolling dice but fails to explain key behaviors: whether results are random, if there are constraints on notation or num_rolls, what the output looks like, or any error handling. This leaves significant gaps for a tool that likely involves randomness and input validation.
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 with the core action and directly ties to the input, making it easy to scan and understand at a glance.
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 low complexity and the presence of an output schema (which should cover return values), the description is somewhat complete for basic use. However, with no annotations and poor parameter semantics, it lacks details on behavior and input handling, making it minimally adequate but with clear gaps for reliable tool invocation.
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 for undocumented parameters. It references 'notation' but doesn't explain its format (e.g., standard dice notation like '3d10') or purpose. It ignores 'num_rolls' entirely, leaving users to guess its role. This adds minimal value beyond the schema's basic property names.
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 states the action ('Roll the dice') and references the input parameter ('with the given notation'), which clarifies the basic purpose. However, it's vague about what 'notation' means (e.g., dice notation like '2d6') and doesn't distinguish this tool from any hypothetical sibling dice tools, though none exist in the provided list.
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 prerequisites, context for rolling dice, or comparisons to other tools like random number generators. Without such information, users must infer usage from the tool name 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 mentions authentication requirements (environment variables), which is useful context. However, it lacks details on critical behaviors such as rate limits, error handling, whether emails are sent immediately or queued, or any side effects (e.g., saving drafts). This leaves significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences that directly state the tool's purpose and prerequisites. It is front-loaded with the main action, and there is no unnecessary information, making it efficient. However, it could be slightly more structured by explicitly listing parameters or usage examples.
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 (a mutation tool for sending emails), the absence of annotations, and the presence of an output schema (which may cover return values), the description is partially complete. It includes authentication details but misses behavioral traits and parameter semantics. For a tool with no annotations and 0% schema coverage, it should provide more context to be fully adequate.
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 description coverage is 0%, so the schema provides no parameter descriptions. The tool description does not mention any parameters (to, subject, body), offering no semantic information beyond what the bare schema titles imply. Since there are 3 parameters, this lack of detail results in a baseline score of 3, as the description fails to compensate for the low coverage.
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 ('Send an email') and the resource ('using Gmail API'), providing a specific verb+resource combination. It distinguishes this tool from siblings like 'read_clipboard' or 'web_search' by focusing on email functionality, though it doesn't explicitly differentiate from non-existent email-related siblings.
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 mentions environment variable prerequisites ('Requires GMAIL_USER and GMAIL_APP_PASSWORD'), which provides some usage context. However, it offers no guidance on when to use this tool versus alternatives (e.g., other email-sending methods or tools), nor does it specify exclusions or typical scenarios for its application.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool searches the web, implying it's a read-only operation that retrieves information, but it lacks details on traits like rate limits, authentication needs, result format, or potential side effects. This is a significant gap for a tool with no annotation coverage.
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, clear sentence with no wasted words. It's front-loaded with the core action ('Search the web') and efficiently conveys the purpose. Every part of the sentence earns its place by specifying the resource and parameter context.
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 one parameter, no annotations, and an output schema exists (which should cover return values), the description is minimally complete. It states what the tool does but lacks behavioral details and usage guidelines. For a simple search tool, it's adequate but has clear gaps in transparency and guidance.
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 'the given query', which aligns with the single parameter 'query' in the input schema. However, schema description coverage is 0%, so the schema provides no additional details. The description adds minimal semantics by implying the query is used for web search, but it doesn't elaborate on query format, constraints, or examples, leaving it somewhat vague.
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 specifies the action is about 'information about the given query'. It distinguishes itself from siblings like read_clipboard or send_gmail by focusing on web search functionality. However, it doesn't explicitly differentiate from potential similar tools (none present in siblings), so it's not a perfect 5.
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, prerequisites, or exclusions, such as when to prefer this over other information sources or tools. With siblings like read_clipboard or roll_dice, there's no explicit comparison or usage scenarios provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the tool writes text to the clipboard on macOS using `pbcopy`, which implies a mutation operation. However, it lacks details on permissions, error handling, or side effects, offering only basic behavioral context.
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 front-loaded with the core action and resource, followed by implementation details. It consists of two concise sentences with no wasted words, making it highly efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers the purpose, platform, and method, though it could benefit from more behavioral details like error cases or limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description must compensate. It adds meaning by explaining that the 'text' parameter is the content to write to the clipboard, which clarifies the parameter's purpose beyond the schema's basic type definition. Since there's only one parameter, this is sufficient for a high score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Write the given text') and target resource ('to the clipboard'), with additional implementation detail ('macOS') and method ('Uses `pbcopy`'). It distinguishes itself from sibling tools like 'read_clipboard' by specifying the write operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'macOS', which suggests this tool is platform-specific. However, it does not explicitly state when to use it versus alternatives (e.g., other clipboard methods or tools) or provide exclusions, leaving some guidance gaps.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the tool reads clipboard text using `pbpaste` on macOS, which implies platform dependency and read-only behavior. However, it lacks details on error handling, permissions needed, or what happens if clipboard is empty, leaving behavioral gaps.
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 extremely concise with two sentences that efficiently convey purpose, platform, and implementation. Every word adds value, and it is front-loaded with the core action, making it highly efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no annotations, but has an output schema), the description is mostly complete. It covers the action, resource, and platform, but could benefit from mentioning the output format or handling edge cases, though the output schema may mitigate this.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description does not add parameter semantics, but this is appropriate given the lack of parameters, warranting a baseline score above 3 for adequate handling.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Read and return') and resource ('current clipboard text'), with platform specificity ('macOS') and implementation detail ('Uses `pbpaste`'). It distinguishes from sibling 'write_clipboard' by being the read counterpart.
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 implies usage context by specifying 'macOS' and the clipboard resource, but does not explicitly state when to use this tool versus alternatives like 'write_clipboard' or other data retrieval methods. It provides clear context but lacks explicit exclusions or alternatives.
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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