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datafe

Quick Chart MCP Server

by datafe
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TypeScript
Hybrid

Server Quality Checklist

58%
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. The tool's purpose is clearly defined as generating chart image links using Quick Chart API parameters.

    Naming Consistency5/5

    Since there is only one tool, naming consistency is inherently perfect. The tool name 'GetChartImgLink' follows a clear verb_noun pattern, and there are no other tools to compare or create inconsistency with.

    Tool Count2/5

    A single tool is too few for a chart generation server, as it lacks basic operations like creating, updating, or deleting charts, or handling different chart types or configurations. This minimal set limits functionality and forces agents to rely solely on this one tool for all chart-related tasks.

    Completeness2/5

    The tool set is severely incomplete for a chart generation domain. It only provides a way to get chart image links, missing essential operations such as creating, listing, updating, or deleting charts, and lacks support for managing chart templates or configurations, which are typical in such systems.

  • Average 2.9/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 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 Apache 2.0.

  • This repository includes a README.md file.

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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?

    No annotations are provided, so the description must fully disclose behavioral traits. It mentions that parameters follow Quick Chart API, which hints at external behavior, but fails to describe critical aspects like whether this is a read/write operation, authentication needs, rate limits, error handling, or what the output (image link) entails. This leaves significant gaps in transparency for a tool that generates content.

    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 concise and front-loaded in a single sentence, efficiently stating the tool's purpose and parameter reference. However, it could be slightly improved by structuring key details (e.g., separating usage notes) to enhance clarity without adding unnecessary length.

    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's complexity (generating chart images via an external API) and lack of annotations or output schema, the description is incomplete. It does not explain the return value (e.g., format of the image link), error conditions, or behavioral dependencies, leaving the agent with insufficient context 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 input schema has 100% description coverage, with the parameter 'json' documented as using Quick Chart API format. The description adds marginal value by reiterating this and noting the JSON object excludes functions, but does not provide additional syntax, examples, or constraints beyond what the schema implies. This meets the baseline for high schema coverage.

    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: 'draw chart and get chart image link by parameters'. It specifies the verb ('draw chart and get chart image link') and resource ('chart image link'), making the function understandable. However, with no sibling tools mentioned, it cannot demonstrate differentiation from alternatives, which prevents 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 Guidelines2/5

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

    The description provides minimal guidance on when to use this tool, only implying usage through the phrase 'by parameters' and referencing Quick Chart API. It lacks explicit instructions on when to use it versus alternatives, prerequisites, or exclusions, resulting in inadequate guidance for an agent.

    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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