CanIUse MCP

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: check_compatibility for specific feature analysis, generate_configs for build setup, get_fixes for remediation, manage_config for configuration, and scan_project for project-wide analysis. The descriptions clearly differentiate their scopes, making misselection unlikely.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern (e.g., check_compatibility, generate_configs, get_fixes, manage_config, scan_project). The naming is uniform and predictable, using snake_case throughout with clear action-oriented verbs.
Tool Count5/5
With 5 tools, the count is well-scoped for a browser compatibility server. Each tool earns its place by covering distinct aspects of the domain, from checking and scanning to configuration and remediation, without being too sparse or bloated.
Completeness5/5
The tool set provides complete coverage for browser compatibility workflows: checking features, scanning projects, generating configurations, managing settings, and getting fixes. There are no obvious gaps, as it supports the full lifecycle from detection to resolution.
Average 3/5 across 5 of 5 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
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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 'detailed analysis' but doesn't specify what that entails—e.g., output format, performance implications, rate limits, or authentication needs. For a tool with no annotation coverage, this is a significant gap in transparency.
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 a single, efficient sentence that front-loads the core purpose. It avoids redundancy and waste, making it easy to parse. However, it could be slightly more structured by explicitly separating feature and file checks, but this is minor.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits, output format, and usage guidelines. Without annotations or an output schema, the agent is left guessing about the tool's full behavior and results, making this inadequate for effective 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?
Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds minimal value beyond the schema by implying the tool checks 'specific features or files' against 'multiple browser targets,' but it doesn't provide additional syntax, format details, or usage examples. Baseline 3 is appropriate when the schema does the heavy lifting.
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: 'Check specific features or files against multiple browser targets with detailed analysis.' It specifies the verb ('check'), resources ('features or files'), and scope ('multiple browser targets'). However, it doesn't explicitly differentiate from sibling tools like 'scan_project' or 'get_fixes,' which might have overlapping functionality, preventing 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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'scan_project' or 'get_fixes,' nor does it specify prerequisites, exclusions, or typical use cases. This leaves the agent without context for tool selection.
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 'generates' configurations, implying a creation/write operation, but doesn't disclose critical traits like whether this overwrites existing files, requires specific permissions, has side effects, or handles errors. For a tool with no annotations and potential file system impacts, this is a significant gap.
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 unnecessary details. Every word contributes to understanding the tool's function, and there is no redundancy or wasted phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (generating multiple configuration types with 4 parameters) and the absence of both annotations and an output schema, the description is incomplete. It doesn't address behavioral risks, output format, or integration context, leaving significant gaps for an AI agent to infer safe and correct usage.
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 100% description coverage, with all parameters well-documented in the schema itself (e.g., 'configType' with enum values, 'target' as browser target). The description adds no additional parameter semantics beyond what the schema provides, such as explaining interactions between parameters or usage examples. With high schema coverage, the 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 the tool's purpose: 'Generate complete build configurations, CI/CD setups, and workflow files for browser compatibility.' It specifies the verb 'generate' and the resources (configurations, setups, files) with a clear scope (browser compatibility). However, it doesn't explicitly differentiate from sibling tools like 'manage_config' or 'scan_project', which likely have overlapping domains.
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 sibling tools like 'check_compatibility' or 'manage_config', nor does it specify prerequisites, exclusions, or contextual triggers. Usage is implied by the purpose but not explicitly stated.
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 the tool's purpose but doesn't describe what happens during operations (e.g., whether 'reset' is destructive, if changes persist, authentication needs, rate limits, or error conditions). This is inadequate for a tool with 8 parameters and multiple action types.
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 purpose without unnecessary words. It's appropriately sized and front-loaded with the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 8 parameters, multiple action types, and no annotations or output schema, the description is insufficient. It doesn't explain what the tool returns, how different actions behave, or provide enough context for an agent to understand the tool's full scope and limitations.
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?
Schema description coverage is 100%, so the schema already documents all parameters. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions the general categories (baselines, polyfills, overrides) but provides no additional syntax, format details, or usage examples.
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: configuring browser baselines, polyfills, and feature overrides for compatibility checking. It uses specific verbs ('configure') and resources ('browser baselines, polyfills, and feature overrides'), but doesn't explicitly distinguish it from sibling tools like 'generate_configs' or 'check_compatibility'.
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 sibling tools like 'check_compatibility' or 'generate_configs', nor does it specify prerequisites, exclusions, or appropriate contexts for its use.
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. While it mentions what the tool does (analyzing and checking compatibility), it doesn't describe important behavioral aspects: whether this is a read-only operation, what the output format looks like, whether it modifies files, performance characteristics, or error handling. For a scanning tool with 4 parameters and no annotations, this leaves significant 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 a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for the tool's complexity and front-loads the core functionality. Every word earns its place by conveying essential information about what the tool does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a scanning tool with 4 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the output looks like (compatibility reports? feature lists? error summaries?), doesn't mention whether this is a safe read operation, and provides no context about performance or limitations. The agent would be left guessing about important operational aspects.
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?
Schema description coverage is 100%, so the schema already documents all 4 parameters thoroughly with descriptions and defaults. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain relationships between parameters, provide examples beyond what's in the schema, or clarify edge cases. The baseline of 3 is appropriate when the schema does the heavy lifting.
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: 'Analyze project files to detect CSS/JS features and check compatibility across browser targets.' It specifies the verb ('analyze'), resource ('project files'), and what it detects ('CSS/JS features') plus the compatibility checking function. However, it doesn't explicitly differentiate from sibling tools like 'check_compatibility' or 'get_fixes' which might have overlapping functionality.
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 'check_compatibility' or 'get_fixes'. It doesn't mention prerequisites, when-not-to-use scenarios, or how it differs from sibling tools. The agent would have to infer usage from the tool name and description 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?
No annotations are provided, so the description carries full burden. It mentions the types of outputs (remediation steps, polyfills, alternatives) but doesn't disclose behavioral traits like whether this is a read-only operation, potential rate limits, authentication needs, or what happens if features are invalid. For a tool with no annotation coverage, this is insufficient.
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 unnecessary words. Every part earns its place by specifying what is retrieved and for what purpose.
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 no annotations and no output schema, the description is minimally complete for a tool that likely returns informational content. It covers the purpose but lacks details on behavioral aspects and output format, which are important for an agent to use it correctly without structured output 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?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add any meaning beyond what the schema provides about parameters like 'features', 'priority', etc. Baseline 3 is appropriate when the schema does the heavy lifting.
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 verb 'Get' and specifies the resources: 'actionable remediation steps, polyfills, and alternatives for unsupported features'. It distinguishes from siblings like 'check_compatibility' (which likely identifies issues) by focusing on generating solutions rather than detecting problems.
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 after compatibility issues are identified (via 'from compatibility check results' in the schema), suggesting it follows 'check_compatibility'. However, it doesn't explicitly state when to use this tool versus alternatives like 'generate_configs' or 'manage_config', leaving some ambiguity about workflow context.
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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