Skip to main content
Glama
goofrey

Zoom Search

by goofrey
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v0.1.6

  • Disambiguation5/5

    With only one tool, there is no risk of ambiguity; the tool's purpose is entirely distinct by default.

    Naming Consistency5/5

    The single tool uses a clear snake_case naming convention, which is consistent by default.

    Tool Count3/5

    The server has only one tool, which is on the low end of tool count. While it serves a focused purpose, it feels slightly thin for a server that could potentially offer more related operations.

    Completeness4/5

    The single tool covers the core search functionality and returns comprehensive results (answer, sources, warnings, metrics, evidence). However, there might be missing features like search configuration or history, but the current scope is reasonable.

  • Average 2.7/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 45 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.

  • 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.

  • 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

  • Behavior3/5

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

    The description enumerates the types of outputs (answer, sources, warnings, metrics, evidence), which partially reveals behavior. However, no annotations exist, and the description does not disclose side effects, authorization needs, rate limits, or whether the tool is destructive. For a search-like tool, this is acceptable but incomplete.

    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 a single sentence, achieving brevity. It front-loads the action and lists outputs. However, it could be more informative without increasing length, e.g., by noting the search technology or providing a hint about required parameters.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool complexity (9 parameters, 1 required, 0% schema coverage), the description is far from complete. An output schema exists, which helps for return types, but the parameter semantics gap and lack of usage guidance leave the description insufficient for an agent to effectively invoke the tool.

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

    Parameters1/5

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

    With 0% schema description coverage and 9 parameters, the description offers no explanation of any parameter. It does not mention the required 'question' parameter or optional ones like 'seed', 'output_mode', or numer results. This severely hampers correct invocation.

    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 action ('Run Zoom Search') and the outputs (answer, sources, warnings, metrics, evidence). It is specific about the return value composition, which helps the agent understand the purpose. However, without sibling tools, differentiation is not tested, and 'Zoom Search' is not elaborated, so it is not a 5.

    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?

    The description provides no guidance on when to use this tool, prerequisites, or alternatives. There is no mention of context or exclusionary criteria, leaving the agent with no usage heuristics beyond the name.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

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.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

zoom-search MCP server

Copy to your README.md:

Score Badge

zoom-search MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/goofrey/zoom-search'

If you have feedback or need assistance with the MCP directory API, please join our Discord server