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jeel00dev

Excalidraw MCP Server

by jeel00dev
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Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clear, non-overlapping purpose: checking server status, generating a diagram, and listing previously generated diagrams. No ambiguity in choosing which tool to use.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (check_llm_status, generate_diagram, list_diagrams), making them predictable and easy to understand.

    Tool Count5/5

    With only 3 tools, the server is tightly focused on diagram generation and management. Each tool serves a distinct need without unnecessary bloat, perfectly scoped for its purpose.

    Completeness4/5

    The core workflows are covered: health check, diagram creation, and listing past diagrams. Missing deletion is a minor gap, but the server still fulfills its primary function effectively.

  • Average 4.1/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 22 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.

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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.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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

    Then . Browse examples.

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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

  • Behavior3/5

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

    No annotations provided, so description carries burden. Discloses save location (~/excalidraw_diagrams/) and allowed diagram types, but lacks details on overwrite behavior, permissions, or side effects.

    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?

    Concise docstring format with front-loaded purpose. No redundant information, but the Args section somewhat duplicates the schema.

    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?

    Covers key aspects: purpose, parameters, output location, example. But missing behavioral details like file overwrite, error handling, and output format (though output schema exists but unknown).

    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 has 0% coverage, so description compensates well: explains description parameter with example, lists diagram_type options, and clarifies filename extension and save location. Could be more precise about allowed diagram_type values.

    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?

    Clearly states it generates an Excalidraw diagram from natural language, with an example. Distinguishes from siblings (check_llm_status, list_diagrams) by being the only diagram generation tool.

    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?

    Implied usage from description, but no explicit when-to-use or when-not-to-use guidance. No comparisons with alternatives, though siblings are unrelated.

    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?

    No annotations provided. The description indicates a read-only check operation, but does not describe behavior like timeout, error handling, or what constitutes 'reachable'. However, it is not misleading.

    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?

    A single sentence that conveys the full purpose with no extraneous words. It is front-loaded and 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 no parameters and the existence of an output schema, the description is mostly complete. It could mention the expected return value format (e.g., boolean or status object), but the output schema presumably covers that.

    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?

    There are no parameters, so schema coverage is 100%. The description adds meaning beyond the schema by explaining the tool's purpose. With zero parameters, baseline is 4.

    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 checks if a local llama.cpp server is running and reachable. It uses a specific verb ('check') and resource ('local llama.cpp server'). This purpose is distinct from sibling tools (generate_diagram, list_diagrams).

    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?

    No explicit guidance on when to use or alternatives. The context implies usage before other server-dependent tools, but the description does not state this. No exclusions or alternatives are given.

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

  • Behavior4/5

    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 lists diagrams previously generated by this server, implying read-only behavior. However, it does not elaborate on ordering, pagination (if any), or authorization. Given the tool's simplicity, this is adequate.

    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 sentence that immediately conveys the tool's purpose. It is concise and front-loaded with no wasted words.

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

    Completeness5/5

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

    Given zero parameters and an existing output schema, the description provides all necessary information for an agent to understand and invoke the tool correctly. It is complete for its complexity.

    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?

    There are zero parameters, and schema coverage is 100%. The description has no need to explain parameters. Per guidelines, a baseline of 4 is appropriate for tools with no parameters.

    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 verb ('list') and resource ('all Excalidraw diagrams previously generated by this server'). It distinguishes from sibling tools: generate_diagram creates diagrams, check_llm_status checks LLM status, so there is no ambiguity.

    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?

    Although the description does not explicitly state when to use this tool versus alternatives, the context makes it obvious: it lists all diagrams, while siblings create or check status. The simplicity means the purpose is self-evident, but a slight lack of explicit guidance prevents a 5.

    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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