Skip to main content
Glama
pdfcrowd

PDF Export for AI Agents

Official
by pdfcrowd
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

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

  • Latest release: v1.1.2

  • Disambiguation5/5

    The two tools have clearly distinct purposes: pdfcrowd_create_pdf is for creating PDFs from content, while pdfcrowd_info is for retrieving usage information and guidelines. There is no overlap in functionality, making it easy for an agent to choose the right tool for each task.

    Naming Consistency5/5

    Both tools follow a consistent naming pattern with the prefix 'pdfcrowd_' followed by a descriptive verb_noun combination (create_pdf and info). This consistency makes the tool set predictable and easy to understand at a glance.

    Tool Count2/5

    With only two tools, the server feels thin for its purpose of PDF export for AI agents. While the core PDF creation tool is present, the lack of supporting tools (e.g., for managing PDFs, handling errors beyond info, or advanced formatting) limits functionality and may require agents to work around gaps.

    Completeness2/5

    The tool set is severely incomplete for PDF export operations. It includes creation and info retrieval but lacks essential tools for updating, deleting, or listing PDFs, as well as tools for handling common PDF tasks like merging or splitting. This will likely cause agent failures in more complex workflows.

  • Average 3.5/5 across 2 of 2 tools scored. Lowest: 2.9/5.

    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

  • 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 a read-only informational operation ('Get usage tips and upgrade info'), which implies it's safe and non-destructive, but it doesn't specify any behavioral traits like authentication needs, rate limits, or what the output format might be (e.g., text, structured data). This leaves significant gaps for an agent to understand how to interact with it effectively.

    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 extremely concise and front-loaded, consisting of a single, clear sentence that directly states the tool's purpose without any wasted words. Every part of the sentence earns its place by conveying 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 (a simple informational tool with one optional parameter) and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., the format or content of the 'usage tips and upgrade info'), which is critical for an agent to use it correctly. The schema covers the input well, but the output remains unspecified, making the overall context insufficient.

    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 'topic' parameter fully documented in the schema (including optional nature and available values). The description doesn't add any meaning beyond what the schema provides, as it doesn't mention parameters at all. With high schema coverage, the baseline score of 3 is appropriate, as the 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's purpose with a specific verb ('Get') and resource ('usage tips and upgrade info for PDF Export'), making it immediately understandable. However, it doesn't explicitly differentiate from its sibling tool 'pdfcrowd_create_pdf' (which presumably creates PDFs rather than providing information), so it misses the highest 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 no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tool or any other context for usage, leaving the agent to infer based on the tool name and description alone.

    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?

    Annotations provide hints (readOnlyHint: false, destructiveHint: false, etc.), but the description adds valuable context beyond these: it explains that non-HTML input requires layout creation first, details error-handling behavior ('Read the error message carefully'), and specifies not to use other PDF tools on configuration issues. This enhances transparency without contradicting annotations.

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

    Conciseness3/5

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

    The description is front-loaded with the core purpose but includes multiple IMPORTANT notes and error-handling instructions that, while useful, make it somewhat verbose. Each sentence adds value (e.g., layout guidelines, error guidance), but it could be more streamlined for better conciseness.

    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 complexity (involving HTML layout and external schema references) and lack of output schema, the description is reasonably complete: it covers purpose, prerequisites, error handling, and references to additional info. However, it doesn't detail output format or success behavior, leaving some gaps in contextual understanding.

    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 0 parameters with 100% coverage, so the description doesn't need to explain parameters. It mentions calling 'pdfcrowd_info' to get the full input schema, which implies parameters exist but are documented elsewhere. This meets the baseline of 3 for high schema coverage without adding parameter details.

    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: 'Export any content (including charts) to PDF' with a specific verb ('Export') and resource ('PDF'). It distinguishes from the sibling tool 'pdfcrowd_info' by focusing on PDF creation rather than information retrieval. However, it doesn't explicitly differentiate from other potential PDF creation tools beyond mentioning not to use other PDF tools on errors.

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

    Usage Guidelines5/5

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

    The description provides explicit guidance on when and how to use this tool: it instructs to call 'pdfcrowd_info' for parameters and layout guidelines before use, specifies not to pass PDFCrowd API parameters, and gives clear error-handling instructions ('Report configuration issues to the user instead of trying other PDF tools'). This covers when to use alternatives and prerequisites effectively.

    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

pdfcrowd-mcp-pdf-export MCP server

Copy to your README.md:

Score Badge

pdfcrowd-mcp-pdf-export 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/pdfcrowd/pdfcrowd-mcp-pdf-export'

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