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mambalabsdev

Workplace Program Detector MCP Server

by mambalabsdev

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    Only one tool exists, so there is no possibility of confusion or overlap. The tool's purpose is clear and distinct.

    Naming Consistency5/5

    With a single tool, naming is trivially consistent. The verb_noun pattern (detect_workplace_programs) is clear and descriptive.

    Tool Count3/5

    The server has only one tool, which is borderline for a typical MCP server. However, the narrow, focused purpose of detecting workplace programs justifies a single, comprehensive tool.

    Completeness5/5

    The tool thoroughly covers the domain of detecting publicly published workplace programs by reading both job postings and website pages. It includes options to skip discovery, force refresh, and explains limitations, providing a complete read-only workflow.

  • Average 4.8/5 across 1 of 1 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
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • 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

  • Behavior5/5

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

    The description adds extensive behavioral context beyond the annotations: it reads two independent paths, caches results for 14 days, requires an APIFY_TOKEN, consumes credits, and clarifies that absence of a signal does not mean the program doesn't exist. This is highly transparent and aligns with the readOnlyHint, idempotentHint, and openWorldHint.

    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 detailed yet efficient, with each sentence contributing necessary context: purpose, two data paths, parameter usage, caching, and interpretation of results. It is front-loaded with the core purpose and organized logically.

    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?

    Even without an output schema, the description explains the return shape (one flat row per domain), covers all six parameters implicitly, and discloses operational requirements (APIFY_TOKEN, credits) and limitations. This makes it fully self-contained for correct invocation.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Although the schema covers all parameters, the description enriches several: it explains why ats_slug skips discovery, what skipCache does, and how scan_web_pages and scan_job_postings offer complementary signal paths. This adds practical meaning beyond the schema field 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 what the tool does: detects which people programs a company publishes on its own surfaces, returning one flat row per domain. It specifies the exact resources (job postings via ATS, website pages) and distinguishes this from merely reporting on actual programs, making the purpose unambiguous even without siblings.

    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 on when to use the tool and its sub-paths (e.g., turning off either scan path, using ats_slug to skip discovery). It doesn't explicitly mention alternative tools or when not to use it, but given the absence of siblings, this is sufficient.

    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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