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harche

ProDisco

by harche
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TypeScript
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Server Quality Checklist

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

  • Latest release: v1.0.1

  • Disambiguation5/5

    The two tools have entirely distinct purposes: one searches API documentation, the other executes code. No overlapping functionality.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun camelCase pattern (prodisco_runSandbox, prodisco_searchTools).

    Tool Count3/5

    Two tools is minimal, but the server's scope is narrow (sandbox execution + API discovery). The runSandbox tool is complex with many modes, justifying a small set.

    Completeness4/5

    The sandbox execution covers all major modes (execute, stream, async, test) and the search tool is present. Minor gaps like script management are missing, but the core workflow is complete.

  • Average 4.4/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 0 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.

  • Add a glama.json file to provide metadata about your server.

  • 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.

  • Add related servers to improve discoverability.

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 provided, the description carries full burden. It discloses that the tool searches indexed TypeScript typings or falls back to ESM exports, and that it does not execute code or call external services. The behavior is transparent, though it does not describe the return format or pagination details.

    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 well-structured with a bold main statement and bullet points for libraries. It is somewhat redundant because the library list appears both in the description and in the library parameter description, but overall it is not overly verbose.

    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's complexity (7 parameters, nested objects, no output schema), the description covers the search scope, indexed libraries, filter options, and explicitly states it does not execute code. It is sufficiently complete for an agent to understand the tool's capabilities.

    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 context by listing indexed libraries and explaining filter categories, but the schema already provides detailed parameter descriptions. The added value is modest.

    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 browses API documentation for TypeScript libraries, using specific verb 'browse' and resource 'API documentation'. It differentiates from the only sibling tool by explicitly stating it does not execute code.

    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 when to use (to search for methods/types/functions by name) and implicitly contrasts with the sibling by stating no code execution. It could be more explicit about when to use the alternative tool, but the context is clear.

    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?

    No annotations provided, so description carries full burden. It discloses sandbox restrictions, allowed imports, pre-injected globals, caching behavior, and details of each mode (blocking, streaming, async, etc.). No contradiction.

    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?

    Well-structured with sections (PREREQUISITE, IMPORTANT, BEST PRACTICE, MODES, ALLOWED IMPORTS). Front-loaded with critical info. Some repetition of test details from schema, but overall each sentence adds value.

    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?

    Comprehensive coverage of prerequisites, usage, parameters, and restrictions for a complex tool. Lacks output examples, but no output schema is provided. Completeness is high given the constraints.

    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. Description adds value by reinforcing caching requirement for scriptName, providing naming conventions, and detailing test globals (test, assert) beyond schema. This extra guidance elevates it above baseline.

    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 executes TypeScript code in a sandboxed environment, specifies multiple modes, and explicitly mentions prerequisite call to searchTools, distinguishing it from the sibling tool. Verb and resource are clear.

    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 instructs to call searchTools first, provides best practices for caching and testing, and describes when to use each mode. No ambiguity about when to use this tool vs alternatives.

    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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