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pucilpet

crawlgraph-mcp

by pucilpet

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.2.2

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: backlinks for single domain lookup, gap_analysis for competitor gap detection, gap_outreach_targets for ranked outreach targets, and releases for listing data snapshots. No overlap.

    Naming Consistency5/5

    All tool names follow a consistent pattern of lowercase with underscores, using descriptive noun phrases (e.g., gap_analysis, gap_outreach_targets). No mixing of conventions.

    Tool Count5/5

    With 4 tools, the set is well-scoped for a specialized backlink analysis server. Each tool is necessary and the count is appropriate for the domain.

    Completeness4/5

    Covers essential workflows: single domain lookup, competitor gap analysis, and enriched outreach targeting. Missing bulk queries or historical comparisons, but the releases tool enables snapshot selection, mitigating gaps.

  • Average 4.4/5 across 4 of 4 tools scored. Lowest: 3.5/5.

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

    • No community issues in the last 6 months
    • 2 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

  • Behavior1/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    Description contradicts the readOnlyHint annotation by explicitly stating it 'costs one gap job against the monthly quota', which is a side effect. This is a clear contradiction, so score is 1 per rubric.

    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?

    Three sentences, front-loaded with purpose, then async behavior, quota, and output. Every sentence adds value with no fluff.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Covers purpose, async polling duration, quota cost, and output structure (found_on field). Output schema exists so return details are not required. Complete for 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?

    Schema coverage is 100% with parameter descriptions. The description adds no extra semantic meaning beyond the schema, so baseline of 3 is appropriate.

    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 finds domains linking to competitors but not to you, using specific verb 'run' and resource 'competitor backlink gap analysis'. It distinguishes from sibling tools like 'backlinks' and 'gap_outreach_targets' by its unique focus on gap identification.

    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?

    Usage is implied (run when you want to find backlink gaps) but no explicit when-to-use or when-not-to-use compared to siblings. The quota mention gives cost context but no alternatives are named.

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

  • Behavior5/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds useful behavioral context: the data source (Common Crawl webgraph) and quota/cost details, which go beyond annotations. No contradiction with annotations.

    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 three sentences, front-loaded with the main action 'Look up referring domains'. It is concise, avoids fluff, and covers key aspects: action, outputs, source, and cost.

    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?

    The description covers purpose, outputs, data source, and quota, and the schema and annotations handle parameters and safety. It is mostly complete, though it could optionally mention error handling or behavior for missing domains.

    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 explains each parameter. The description adds minor context (data source, quota) but does not significantly enhance parameter understanding beyond what the schema provides. Baseline 3 is appropriate.

    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 looks up referring domains (backlinks) for a single target domain, specifying the returned data (linking domain, host count, authority score, target authority/rank). This distinguishes it from sibling tools like gap_analysis and gap_outreach_targets, which serve different purposes.

    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 mentions the cost (one backlinks call against monthly quota), giving context on usage limits. However, it does not explicitly state when not to use or offer direct alternatives, though the context implies it's for obtaining backlink data.

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

  • Behavior5/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    Beyond annotations (readOnlyHint, idempotentHint, destructiveHint false), the description adds that the tool runs a gap analysis, filters platform/CDN noise, scores by authority, and has a cost model. No contradictions with annotations.

    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 concise (3 sentences plus a usage note) and front-loaded with purpose. Every sentence provides essential information about how the tool works and its usage.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the presence of an output schema (which presumably details return values), the description covers the algorithm, filtering, scoring, and cost. It is sufficient for an agent to understand what the tool does and its inputs.

    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 description coverage is 100%, so the schema already defines each parameter. The description adds value by explaining the overall algorithm (ranking, filtering) and the purpose of enabling options, which goes beyond the schema.

    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 runs a gap analysis and ranks results into priority and secondary based on competitor linking patterns. It distinguishes itself from sibling tools like gap_analysis and backlinks by focusing on outreach target generation.

    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 provides context by calling it 'the warm-outreach play' and recommending 2-3 competitors. It also mentions costs (gap job + backlinks calls). However, it does not explicitly contrast with siblings or state when not to use.

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

  • Behavior5/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds that it does not count against quota, a behavioral trait beyond annotations. No contradictions.

    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 concise sentences, first states purpose and quota, second gives usage hint. No wasted words, front-loaded.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given simplicity (no parameters, output schema exists), description sufficiently covers purpose, quota, and usage flow. Complete for a list operation.

    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?

    No parameters exist, so schema coverage is 100%. Per rubric, 0 params baseline 4. Description adds no parameter info, but none needed.

    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 'List the Common Crawl releases the API can query', a specific verb and resource. It distinguishes from siblings like 'backlinks' which uses a release id.

    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?

    Explicitly mentions that the tool does not count against quota and guides to 'Use a release id with the backlinks tool to query a specific snapshot', providing clear when-to-use and 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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