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czottmann

kagi-kan-mcp

by czottmann
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

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

  • Latest release: v1.3.0

  • Disambiguation5/5

    The two tools serve entirely different purposes: one for fetching web search results, the other for summarizing content from a URL. There is no overlap or ambiguity.

    Naming Consistency5/5

    Both tools use a consistent 'kagi_<action>' pattern (kagi_search_fetch and kagi_summarizer), making the naming predictable and easy to follow.

    Tool Count4/5

    With only two tools, the server is minimal but still covers its core capabilities of search and summarization. Each tool earns its place, though the count is slightly below the typical 3-15 range.

    Completeness4/5

    The tool set covers the fundamental operations for the server's purpose: searching the web and summarizing content. Minor gaps like additional result filtering or multiple summary modes exist, but the core workflow is complete.

  • Average 4.1/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • 0 of 1 community issues answered or closed in the last 6 months
    • 0 commits in the last 12 weeks
    • Last stable release on
    • 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, the description must bear full burden. It mentions the API and broad document support but does not disclose rate limits, auth needs, or error scenarios. Basic behavior is covered but lacks depth.

    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?

    Two sentences, front-loaded with core purpose, no redundant information. Efficient and to the point.

    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?

    For a tool with 3 parameters and no output schema, the description covers purpose and capability well. Lacks output format hint or limitations, but overall adequate given simplicity.

    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?

    Schema coverage is 100%, so baseline is 3. The description adds value by stating the tool handles any document type (webpage, video, audio), providing context beyond the schema's parameter descriptions.

    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 summarizes content from a URL using Kagi API, specifying support for any document type. It differentiates from the sibling tool 'kagi_search_fetch' which likely retrieves search results.

    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 general usage ('summarize any document type') but provides no explicit guidance on when to use this tool versus the sibling 'kagi_search_fetch', nor exclusions or prerequisites.

    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?

    No annotations are provided, so the description carries the full burden. It explains that results from multiple queries are merged and numbered continuously, which is helpful beyond the schema. However, it does not disclose auth requirements, rate limits, or error behavior, leaving 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 composed of three concise sentences, each adding necessary information. It front-loads the purpose and provides essential behavioral details without fluff. Every sentence earns its place.

    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 simplicity of the tool, the description covers the main purpose and behavior. However, with no output schema, it lacks details about the response structure (e.g., result fields), which an agent may need to interpret results. It is adequate but not fully complete for a tool with no annotations.

    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?

    Schema coverage is 100%, so baseline is 3. The description adds value by explaining how the queries parameter affects output (combined, numbered), which is not in the schema. The limit parameter description in the text is redundant with the schema, but the added context for queries raises the 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 tool fetches web results using Kagi search, specifying the action ('fetch') and resource ('web results'). It also provides a specific usage hint ('when the user tells you to fetch'), which distinguishes it from general tasks.

    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 explicitly says 'Use for general search and when the user explicitly tells you to fetch results/information.' This gives clear context for when to invoke, though it does not mention alternatives or when not to use, missing some guidance.

    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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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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