Skip to main content
Glama
banned104

Godot MCP Documentation Server

by banned104
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: get_documentation_file retrieves specific file content, while get_documentation_tree provides a structural overview. There is no overlap in functionality, making it impossible for an agent to confuse them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with 'get_' prefix and snake_case naming. The naming is perfectly predictable across the tool set, with no deviations in style or convention.

    Tool Count3/5

    With only 2 tools, the server feels thin for a documentation server that might benefit from additional operations like search, navigation, or metadata retrieval. While the tools cover basic reading and browsing, the count is borderline minimal for the apparent scope.

    Completeness3/5

    The server provides core read operations (get file, get tree) but lacks obvious enhancements like search functionality, content filtering, or version-specific documentation access. The surface is functional but incomplete for comprehensive documentation interaction, leaving notable gaps in typical documentation workflows.

  • Average 3.9/5 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
    • 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.

  • 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

  • Behavior3/5

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

    No annotations are provided, so the description carries the full burden. It discloses that the tool returns a 'directory tree representation' as a string, which is useful behavioral context. However, it doesn't mention potential limitations like depth, formatting, or performance aspects. The description adds value but lacks comprehensive behavioral 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 clear sections (Returns, Usage Examples, Note) and is front-loaded with the core purpose. It's concise, with each sentence adding value, though the usage example could be slightly more informative. Minimal waste, but not perfectly efficient.

    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 simplicity (0 parameters, output schema exists), the description is reasonably complete. It explains what the tool does, provides a return type, and references related tools. However, it could benefit from more detail on the tree format or edge cases, keeping it from a perfect score.

    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 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing on the tool's function. A baseline of 4 is applied since there are no parameters to document, and the description doesn't add unnecessary param info.

    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 tool's purpose: 'Get a tree-style overview of the documentation folder.' It specifies the verb ('Get') and resource ('documentation folder'), and distinguishes it from the sibling tool get_documentation_file by mentioning that files are exposed via that other tool. However, it doesn't explicitly contrast the two tools' purposes beyond this mention, keeping it from a perfect score.

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

    Usage Guidelines3/5

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

    The description provides some usage context by noting that files are exposed via get_documentation_resource, implying this tool is for overview rather than file access. It includes a usage example, but lacks explicit guidance on when to use this tool versus alternatives (e.g., no clear 'when-not' scenarios). The guidelines are implied rather than explicit.

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

  • Behavior3/5

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

    With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns content or an error message, which covers basic success/failure behavior, but lacks details on permissions, rate limits, or other operational constraints. It adequately describes the core behavior but misses advanced contextual information.

    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 well-structured with clear sections (description, args, returns, usage example), front-loaded with the core purpose, and every sentence adds value without redundancy. It efficiently communicates essential information in a compact format.

    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 low complexity (1 parameter, no nested objects) and the presence of an output schema (which handles return value documentation), the description is mostly complete. It covers purpose, parameter semantics, and basic behavior, but could improve by addressing error handling details or constraints like file size limits.

    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 schema description coverage is 0%, so the description must compensate. It explains the 'file_path' parameter with a clear example ('classes/class_camera2d.md') and specifies it's relative to the docs directory, adding meaningful context beyond the bare schema. However, it does not detail allowed file types or path validation rules.

    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 specific action ('Get the content') and resource ('a specific documentation file'), distinguishing it from the sibling tool 'get_documentation_tree' which presumably retrieves a directory structure rather than file content. The verb+resource combination is precise and unambiguous.

    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 for when to use this tool (to retrieve file content) and includes a usage example, but it does not explicitly state when NOT to use it or mention the sibling tool as an alternative for different needs. The example helps clarify the intended use case.

    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

godot-docs-mcp MCP server

Copy to your README.md:

Score Badge

godot-docs-mcp 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/banned104/godot-docs-mcp'

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