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emirhanyenici

SEO Optimizer MCP Server

by emirhanyenici
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Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clear, non-overlapping purpose: fetch_page retrieves HTML, pagespeed provides performance metrics, and serp fetches search results. No ambiguity.

    Naming Consistency4/5

    Names mostly follow verb_noun (fetch_page) but pagespeed is a proper noun and serp is an acronym, causing slight inconsistency. However, they are still readable.

    Tool Count4/5

    3 tools is reasonable for a focused SEO server, covering core functionalities without being overly minimal or excessive.

    Completeness3/5

    Covers essential SEO tasks (page fetch, performance, rankings) but lacks tools for backlinks, keyword suggestions, or site audits, leaving notable gaps.

  • Average 3.6/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 1 commit 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 to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?

    With no annotations, the description should disclose behavioral traits. It only states the output content (metrics and opportunities). No information on whether it runs a live test, caching behavior, authentication needs, or rate limits.

    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?

    Single sentence efficiently conveys purpose and key details. No unnecessary words, front-loaded with main function.

    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?

    For a simple tool with two parameters and no output schema, the description covers basic intent. However, it lacks details on return format or how results are structured, which would aid an agent.

    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%, so baseline is 3. The description adds no extra meaning beyond the schema; the schema already describes url and strategy well.

    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 provides a PageSpeed Insights/Lighthouse summary including specific Core Web Vitals and performance opportunities. It distinguishes implicitly from siblings (fetch_page, serp) by focusing on performance, but lacks explicit differentiation.

    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?

    No guidance on when to use this tool vs siblings. The description only explains output; no context on prerequisites, when not to use, or alternative tools.

    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?

    Discloses the two backends (SerpAPI with key, DuckDuckGo fallback) and the 'source' field in output. However, lacks details on rate limits, key availability consequences, or error cases. Without annotations, the description does a reasonable job but could be more thorough.

    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 with no filler. Front-loaded with core purpose, then adds behavioral detail. Every sentence earns its place.

    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?

    Output is described (URLs, titles, descriptions, positions, source field), which is adequate given no output schema. Missing details on result limit enforcement, pagination, or data format, but the tool is simple and the description covers the essentials.

    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 each parameter. The description adds no additional parameter-specific meaning beyond the schema. 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?

    Description clearly states it returns organic search results (URLs, titles, descriptions, positions) for a keyword, distinguishing it from sibling tools fetch_page (single page content) and pagespeed (performance metrics).

    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?

    No explicit guidance on when to use this tool versus fetch_page or pagespeed. The fallback behavior is mentioned but not contextualized as a consideration. The agent is left to infer usage from the description alone.

    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 full behavioral disclosure burden. It discloses that output is cleaned HTML (scripts, styles, attributes stripped). However, it does not mention potential limitations like size limits, encoding handling, or error behavior.

    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, consisting of two sentences with no unnecessary words. It front-loads the primary action and includes useful examples efficiently.

    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 low complexity (single parameter, no output schema, no annotations), the description is fairly complete. It explains the tool's purpose and output. It could be improved by specifying the return format (e.g., 'returns a string of cleaned HTML') but is 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?

    Schema description coverage is 100%, so the description does not need to add much. The tool description just says 'Fetch a URL' which repeats the schema's 'The URL to fetch' without adding additional meaning or constraints.

    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 'Fetch', the resource 'URL', and the output 'cleaned, readable HTML' with specifics of stripping scripts, styles, attributes. It gives examples of use cases (target page, competitor pages, robots.txt, sitemap.xml), distinguishing it from siblings like 'pagespeed' and 'serp'.

    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 clear context for when to use the tool, listing common use cases. It does not explicitly state when not to use it or compare to alternatives, but the examples imply usage scenarios.

    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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Glama performs regular codebase and documentation scans to:

  • 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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