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Crindo2

GPH Intelligence - Healthcare Vendor Finder

by Crindo2

Server Quality Checklist

83%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: get_provider_detail retrieves full profiles for a specific slug, match_practice provides scored recommendations for a practice profile, and search_providers enables open-ended browsing with filters. Descriptions explicitly indicate when to use each, preventing ambiguity.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case: get_provider_detail, match_practice, search_providers. The naming is predictable and aligns with the functionality.

    Tool Count5/5

    With only 3 tools, the server is well-scoped for its purpose as a healthcare vendor finder. Each tool covers a core operation (browse, match, detail) without unnecessary bloat or deficiency.

    Completeness5/5

    The tool surface covers the full user journey: searching/browsing providers, getting scored matches for a specific practice, and retrieving detailed profiles. No obvious gaps exist for the intended use case.

  • 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
    • 34 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.

  • This repository includes a glama.json configuration file.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

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?

    Annotations already declare readOnlyHint and idempotentHint true, so the tool is clearly a safe read operation. The description adds that it returns an error for unknown slugs, which is useful behavioral context beyond the annotations.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is front-loaded with the main purpose and then details the returned fields. It is slightly verbose with the list of fields, but each sentence adds value. Could be trimmed slightly.

    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 lack of an output schema, the description compensates by listing all key return values. It also provides workflow context (slug from siblings) and error behavior, making it complete for an agent to understand usage.

    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 input schema has 100% coverage, but the description adds value by explaining the slug's origin and format (e.g., 'ams-solutions-inc-dallas-tx') and how it is obtained, which goes beyond the schema's description.

    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 that the tool gets the full profile of one healthcare service provider by slug, listing specific fields. It distinguishes itself from siblings by mentioning that the slug comes from match_practice or search_providers results, which clarifies its role in the workflow.

    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 indicates when to use the tool (after obtaining a slug from sibling tools) and mentions that an error is returned for unknown slugs, implying when not to use. However, it does not explicitly state when alternatives might be preferred.

    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?

    Annotations already declare read-only and idempotent. The description adds value by detailing pagination (page, per_page) and specifying the exact fields returned. It does not mention any destructive or authentication requirements, but those are covered by annotations. A small omission is lack of mention about result ordering or completeness.

    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 four sentences, front-loaded with purpose and return fields. It efficiently separates usage guidance and sibling differentiation. No unnecessary words.

    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 tool complexity (8 params, 1 required) and rich annotations, the description covers the main purpose, output fields, and sibling relationships. It lacks explicit mention of error conditions or ordering, but these are not critical for a browse tool. Overall, it is sufficiently complete for an AI agent to understand selection and invocation.

    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 baseline is 3. The description mentions some parameters (category, location, min_rating) and ties per_page and page to pagination, but adds little extra meaning beyond what the schema already provides. No additional context for tier1_grade or practice_size_fit.

    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 it is a 'paginated browse of the healthcare service provider directory' with specific filters (category, location, minimum quality score) and lists return fields. It also distinguishes from siblings by directing to match_practice for scored recommendations and to get_provider_detail for full profiles.

    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 states when to use this tool ('open-ended exploration and filtering') and when not to ('for scored recommendations to a specific practice profile, use match_practice instead'). Also advises passing a returned slug to get_provider_detail.

    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 and idempotentHint=true, so the agent knows it's safe and idempotent. The description adds behavioral context: returns up to 5 ranked matches, mentions scoring based on EHR compatibility, and outlines the return fields. 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?

    The description is concise and well-structured: it begins with the core purpose, lists return fields, provides usage guidelines, and mentions related tools. Every sentence earns its place with no redundancy.

    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 tool has 7 parameters, no output schema, and moderate complexity, the description is complete. It covers purpose, return structure, when to use versus alternatives, and how to act on results. Annotations handle safety, so no gaps remain.

    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 extra context for the 'ehr_system' parameter ('Helps score providers with compatible integrations higher'), improving understanding beyond the schema. However, it does not add meaning for other parameters, staying at a solid 4.

    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's verb (score and rank), resource (healthcare service providers), and scope (for a specific medical practice profile). It lists the criteria (specialty, size, etc.) and return fields, and explicitly distinguishes from the sibling tool 'search_providers'.

    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?

    Explicit guidance provided: 'Use this when the user has practice-specific criteria and wants scored recommendations — for open-ended browsing, use search_providers instead.' Also tells the user to pass a match's slug to 'get_provider_detail' for the full profile.

    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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