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ukkz

Claude TypeScript MCP Servers

by ukkz
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TypeScript
Hybrid

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: brave_local_search is focused on location-based queries for businesses, services, and attractions, while brave_web_search handles general web searches for current events, news, and broader information. There is no overlap in their intended use cases, making it easy for an agent to choose the correct tool based on the query type.

    Naming Consistency5/5

    Both tools follow a consistent naming pattern with the prefix 'brave_' followed by a descriptive term ('local_search' and 'web_search'), using snake_case throughout. This uniformity makes the tool set predictable and easy to understand, with no deviations in style or structure.

    Tool Count3/5

    With only two tools, the server feels thin for a general-purpose search functionality, as it might lack coverage for specific domains or advanced search capabilities. While the tools are well-defined, a broader scope could benefit from additional tools to handle more nuanced search types or integrations, making the count borderline for the apparent purpose.

    Completeness4/5

    The tool set covers the core search needs with local and web search, providing a good foundation for real-time information retrieval. However, there are minor gaps, such as the absence of tools for specialized searches (e.g., image, video, or academic searches) or advanced filtering options, which agents might need to work around for more complex queries.

  • Average 4.2/5 across 2 of 2 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.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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

  • 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 of behavioral disclosure. It mentions that the tool retrieves 'up-to-date information' and should be used for 'fresh, accurate data,' which implies real-time capabilities but doesn't detail rate limits, authentication needs, or error handling. It adds some context but lacks comprehensive behavioral traits.

    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 appropriately sized and front-loaded, starting with the core purpose. However, it includes repetitive phrases like 'when you need current information' and 'when greater detail would improve your response,' which could be more concise without losing clarity.

    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 complexity (web search with three parameters) and no output schema, the description is fairly complete. It covers purpose, usage guidelines, and context, but lacks details on output format or error handling, which would enhance completeness for an agent invoking the tool.

    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 100%, so the schema already documents all parameters (query, count, offset) with their descriptions. The tool description doesn't add any additional meaning or examples beyond what the schema provides, such as search strategy or query formatting tips, resulting in a baseline score of 3.

    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 tool's purpose: 'Retrieves up-to-date information from the web using Brave Search.' It specifies the verb ('retrieves'), resource ('information from the web'), and distinguishes it from the sibling tool 'brave_local_search' by emphasizing web-based, current information rather than local data.

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

    Usage Guidelines5/5

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

    The description provides explicit guidance on when to use this tool, listing specific scenarios such as needing current information beyond knowledge cutoff, answering questions about recent events, or when greater detail would improve responses. It also implicitly distinguishes from alternatives by focusing on web search, though it doesn't explicitly name when not to use it.

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

  • Behavior4/5

    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 effectively describes key traits: it's a search tool (implying read-only, non-destructive), uses real-time data, and is proactive/automatic for certain queries. However, it doesn't mention rate limits, authentication needs, or error conditions, leaving some behavioral aspects unspecified.

    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 appropriately sized and front-loaded, starting with the core purpose. However, it includes some redundancy (e.g., repeating location-based examples) and could be slightly more streamlined without losing clarity. Every sentence adds value, but it's not maximally concise.

    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 moderate complexity (2 parameters, no output schema, no annotations), the description is largely complete. It covers purpose, usage, and behavioral context well. The main gap is the lack of output format details, which is significant since there's no output schema, but the description compensates somewhat by emphasizing the type of information returned (real-time data about places).

    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 fully documents both parameters. The description doesn't add any parameter-specific details beyond what's in the schema (e.g., it doesn't explain 'query' format beyond the schema's example or 'count' constraints beyond the schema's range). This meets the baseline for high schema coverage.

    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 tool's purpose with specific verbs ('finds information') and resources ('local businesses, services, attractions, locations'), and explicitly distinguishes it from its sibling tool by emphasizing its focus on real-time local data versus the broader 'brave_web_search'. It provides concrete examples of what it searches for.

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

    Usage Guidelines5/5

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

    The description explicitly states when to use this tool ('whenever a query mentions specific places or location-based information') and provides detailed examples of use cases (e.g., questions about restaurants, 'near' queries, business hours). It also contrasts with alternatives by noting it provides 'more accurate and up-to-date information than your built-in knowledge', though it doesn't explicitly name the sibling tool as an alternative.

    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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