Skip to main content
Glama
ValentinTarnovsky

Minecraft Plugin Documentation MCP Server

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.1

  • Disambiguation4/5

    The tools have mostly distinct purposes with clear boundaries: analyze_plugin_project focuses on comprehensive project analysis, check_latest_versions handles version checking, get_dependency_docs retrieves documentation, and scan_project_dependencies extracts dependency lists. However, analyze_plugin_project and scan_project_dependencies have some overlap in scanning dependencies, which could cause minor confusion.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case throughout: analyze_plugin_project, check_latest_versions, get_dependency_docs, and scan_project_dependencies. The naming is predictable and readable without any deviations or mixed conventions.

    Tool Count4/5

    With 4 tools, the count is reasonable for a server focused on Minecraft plugin documentation and dependency management. It covers key areas like analysis, version checking, documentation retrieval, and dependency scanning, though it might feel slightly thin for broader plugin development workflows.

    Completeness3/5

    The tool set covers core aspects of dependency management and documentation for Minecraft plugins, but there are notable gaps. It lacks tools for creating or updating dependencies, managing plugin configurations, or integrating with development environments, which could limit agent workflows in more complex scenarios.

  • Average 3.5/5 across 4 of 4 tools scored.

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

    • No community issues in the last 6 months
    • 5 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
  • Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.

    If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.

    MCP servers without a LICENSE cannot be installed.

  • 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

  • Behavior2/5

    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 mentions scanning, extracting, checking, and recommending, but lacks details on permissions required, whether it modifies files, rate limits, output format, or error handling. For a tool with potential file system access and analysis operations, this leaves significant behavioral gaps.

    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, efficient sentence that front-loads the main purpose and lists key actions without redundancy. It could be slightly more structured by separating core functions, but it avoids waste and is appropriately sized for the tool's scope.

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

    Completeness3/5

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

    Given no annotations and no output schema, the description provides a basic overview but lacks completeness for a tool with file system interaction and analysis outputs. It covers the 'what' but not the 'how' or 'what next', such as result format or error cases, leaving gaps in contextual understanding despite the clear schema coverage.

    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 schema already documents both parameters thoroughly. The description adds no additional parameter semantics beyond implying 'project_path' is for analysis and 'check_versions' relates to dependency updates, which the schema already covers. Baseline 3 is appropriate when schema does the heavy lifting.

    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 performs a 'comprehensive analysis' of a Minecraft plugin project, specifying actions like scanning subprojects, extracting dependencies, checking for updates, and providing recommendations. It distinguishes from siblings by covering multiple analysis aspects rather than focusing on specific tasks like version checking or documentation retrieval, though it doesn't explicitly contrast with each sibling.

    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 implies usage for analyzing plugin projects with dependency and update concerns, but provides no explicit guidance on when to use this tool versus alternatives like 'check_latest_versions' or 'scan_project_dependencies'. It suggests a broad analysis context without detailing prerequisites, exclusions, or comparative scenarios.

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

  • Behavior2/5

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

    With no annotations provided, the description carries full burden. It describes the core operation but lacks important behavioral details: whether the scan is recursive, what happens if files are missing or malformed, whether it modifies files, error handling, or performance characteristics. The description doesn't contradict annotations (none exist), but provides minimal behavioral context.

    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?

    Two sentences that efficiently convey purpose and outcome with zero wasted words. The first sentence states what the tool does, the second describes the return value. Perfectly front-loaded and appropriately sized for the complexity.

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

    Completeness3/5

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

    For a single-parameter tool with no annotations and no output schema, the description adequately covers the basic operation but lacks completeness. It doesn't explain the structure of the returned dependency list, error conditions, or important behavioral constraints. The description compensates somewhat but leaves significant gaps for a tool that performs file system operations.

    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% (the single parameter 'project_path' is fully documented in the schema). The description doesn't add any parameter-specific information beyond what the schema provides, such as path format expectations or validation rules. With high schema coverage, baseline 3 is appropriate.

    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 ('scan', 'extract'), the target resource ('Minecraft plugin project directory'), and the specific files processed ('build.gradle, build.gradle.kts, and pom.xml files'). It distinguishes from siblings by focusing on dependency extraction rather than analysis, version checking, or documentation retrieval.

    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 implies usage context (when you need to extract dependencies from specific build files), but doesn't explicitly state when to use this tool versus alternatives like 'analyze_plugin_project' or 'check_latest_versions'. No exclusions or prerequisites are mentioned.

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

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes what the tool does but lacks details on behavioral traits such as whether it requires network access, how it handles errors, if there are rate limits, or what the output format looks like. This is a significant gap for a tool that likely interacts with external resources.

    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 front-loaded and concise, consisting of two sentences that efficiently convey the tool's purpose and usage modes without any wasted words. Every sentence earns its place by providing essential information.

    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 complexity of checking dependencies (which may involve external APIs or repositories) and the lack of annotations and output schema, the description is incomplete. It does not cover behavioral aspects like network requirements, error handling, or output structure, leaving gaps that could hinder an AI agent's ability to use the tool effectively.

    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?

    The description mentions the two modes (checking all or comparing against a project) which aligns with the parameters 'check_all' and 'project_path', but it does not add meaning beyond what the input schema provides. Since schema description coverage is 100%, the baseline score is 3, as the schema already documents all parameters adequately.

    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 ('check for the latest versions') and resource ('Minecraft plugin dependencies'), and distinguishes between two modes: checking all known dependencies or comparing against a project's current versions. This specificity helps differentiate it from sibling tools like 'analyze_plugin_project' or 'scan_project_dependencies'.

    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 the tool: either to check all known dependencies or to compare against a project's current versions. However, it does not explicitly state when not to use it or name alternatives among sibling tools, which would be needed for a perfect score.

    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 describes the return content (URLs, coordinates, version, links, snippets), which is helpful, but doesn't mention potential limitations like rate limits, authentication needs, error handling, or whether it's a read-only operation. It adds some context but lacks comprehensive behavioral details for a tool with no annotation coverage.

    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 a single, well-structured sentence that efficiently conveys the tool's purpose and return values without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every part of the 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?

    Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is reasonably complete. It explains what the tool does and what it returns, which is sufficient for a read operation. However, without annotations or output schema, it could benefit from more behavioral details like response format or error cases, but it's largely adequate for its purpose.

    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 schema already fully documents both parameters ('dependency' and 'fetch_version'). The description doesn't add any parameter-specific details beyond what's in the schema, such as examples of dependency formats or implications of the fetch_version setting. Baseline 3 is appropriate when the schema does the heavy lifting.

    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 action ('Get') and the specific resources ('documentation URLs, Maven coordinates, and latest version for a Minecraft plugin dependency'), including what information is returned ('wiki, javadocs, GitHub links, and quick-start code snippets'). It distinguishes itself from sibling tools like 'analyze_plugin_project' or 'scan_project_dependencies' by focusing on dependency documentation rather than project analysis or version checking.

    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 implies usage when documentation for a Minecraft plugin dependency is needed, but it doesn't explicitly state when to use this tool versus alternatives like 'check_latest_versions' (which might focus only on versions) or 'scan_project_dependencies' (which might list dependencies without documentation). There's no guidance on prerequisites or exclusions, leaving usage context somewhat vague.

    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

MCP-MCP MCP server

Copy to your README.md:

Score Badge

MCP-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/ValentinTarnovsky/MCP-MCP'

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