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matdtools-code

CheckMyLaunch MCP server

by matdtools-code
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Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct purpose: scan_repo scans a repository, scan_url scans a live URL, and get_repair_prompt provides repair instructions. No overlap.

    Naming Consistency5/5

    All tools follow a consistent verb_noun snake_case pattern: scan_repo, scan_url, get_repair_prompt. Highly predictable.

    Tool Count4/5

    Three tools is a reasonable minimal set for a security scanning server. While it could be expanded, the count is appropriate for the core functionality.

    Completeness4/5

    The set covers scanning code (repo) and live sites (URL), plus remediation (repair prompt). A minor gap is lack of result listing or management, but core workflows are covered.

  • Average 4.6/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 3 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 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

  • Behavior4/5

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

    With no annotations, the description carries the burden. It discloses key behaviors: the prompt is safe, no auto-deploy, no secret rotation. Adequate for a read/get operation.

    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: first states purpose and context, second describes output characteristics. 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?

    For a simple get tool with 2 params, no output schema, no annotations, the description fully explains purpose, context, and output safety. Complete.

    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 has 100% coverage. Description adds context that scanId comes from a previous scan result, adding value beyond the schema 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 verb 'get', the resource 'repair prompt for one finding', and the context 'from a previous scan_repo or scan_url result'. It distinguishes from sibling tools by specifying it operates on their results.

    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 explains the output is safe to run as-is, naming exact fix and forbidding unrelated changes. While it doesn't explicitly state when not to use, the context of previous scans is clear.

    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, the description carries full burden. It details what the scan checks (security headers, TLS, etc.) and what it returns (readiness score, findings list), implying a read-only operation. Missing details on rate limits or authentication, but still fairly transparent.

    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 two sentences, front-loading the purpose and checks, then providing usage context. Every sentence is informative with no wasted words.

    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 simple tool (one parameter, no output schema), the description fully explains the tool's function, return values, and intended use case, making it complete for an AI agent.

    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?

    The sole parameter 'url' is well-described in the schema as 'The live site to scan, e.g. https://example.com' and the description adds context about usage. With 100% schema coverage, the description adds value 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 performs a readiness scan on a live website URL, listing specific checks. It is distinct from siblings (scan_repo, get_repair_prompt) by focusing on URL scanning.

    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 recommends using this tool 'to check a deployed site before announcing a launch,' providing clear context. It does not mention when not to use it, but the guidance is sufficient.

    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?

    Without annotations, the description covers the tool's behavior: it scans, returns readiness score and findings list, and lists checked categories. It does not mention potential side effects or limitations like rate limits, but the described behavior is complete for a read-only scan tool.

    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 convey purpose, outputs, usage guidance, and constraint. No redundant information; every sentence adds value.

    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 single parameter, no output schema (output described in text), and related sibling tools, the description fully covers what the tool does, its prerequisites, and its output, providing complete contextual information.

    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?

    The single parameter (repoUrl) is described in the schema (100% coverage), and the tool description adds extra context on format (github.com/<owner>/<repo>) and example URL, enhancing understanding 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 identifies the tool as running a CheckMyLaunch readiness scan on a public GitHub repository, listing specific findings (secrets, risks, deployment problems) and outputs (score and findings list). It distinguishes from siblings (scan_url for generic URLs, get_repair_prompt for repair prompts) by specifying the GitHub repo context.

    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 advises when to use ('after making changes to check safe to ship') and when not ('private repos need signed-in flow'), providing clear usage context and an alternative for private repos.

    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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