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Flux159

MCP Server Modal

by Flux159
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

50%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools, as there are no other tools to confuse it with. The tool's purpose is inherently distinct by default in this minimal set.

    Naming Consistency5/5

    A single tool inherently exhibits perfect naming consistency, as there are no other tool names to compare it against or deviate from. The name 'deploy' follows a clear verb pattern, but consistency is trivially achieved with only one element.

    Tool Count2/5

    A single tool is generally too few for most server purposes, as it limits functionality and suggests an incomplete or overly narrow scope. For a server named 'MCP Server Modal', which implies modal interactions or deployments, one tool feels insufficient to cover meaningful workflows or operations.

    Completeness1/5

    With only a 'deploy' tool, the surface is severely incomplete for any reasonable domain inferred from the server name. There are obvious gaps, such as lacking tools for managing, updating, listing, or deleting deployments, making it impossible for agents to perform basic lifecycle operations without workarounds.

  • Average 1.1/5 across 1 of 1 tools scored.

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

  • This repository is archived. Archived repositories automatically receive an F maintenance tier.

  • Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.

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  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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

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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

  • Behavior1/5

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

    No annotations are provided, so the description carries full responsibility for behavioral disclosure. 'some description' reveals nothing about whether this is a read/write operation, what permissions are needed, side effects, rate limits, or response format. It's completely inadequate for a tool with a potentially significant action like 'deploy'.

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

    Conciseness2/5

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

    While technically concise with just two words, this is a case of harmful under-specification rather than effective brevity. The description fails to communicate any meaningful information, so its conciseness doesn't serve the purpose of helping an AI agent understand the tool.

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

    Completeness1/5

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

    For a tool named 'deploy' with one required parameter, no annotations, no output schema, and 0% schema coverage, the description 'some description' is completely inadequate. It provides no information about what gets deployed, to where, with what consequences, or what the parameter means. This leaves the agent with essentially no usable information.

    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?

    Schema description coverage is 0%, meaning the single parameter 'modal_path' is completely undocumented in the schema. The description 'some description' adds zero information about what this parameter means, what format it expects, or how it influences the deployment. This leaves the parameter entirely unexplained.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose1/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description 'some description' is a tautology that merely restates the tool name 'deploy' without specifying what it actually does. It provides no verb, resource, or scope information, making it completely uninformative about the tool's purpose.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines1/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description offers no guidance on when to use this tool, what context it applies to, or any prerequisites. With no sibling tools mentioned, there's no need for differentiation, but the description fails to provide even basic usage context.

    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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