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GoCanvas MCP Server (read-only)

GoCanvas MCP Server (read-only)

by kbates97
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_submission_default_pdf

Download the default report PDF for a submission and return its content as base64-encoded bytes, using the submission ID.

Instructions

Download the default Report PDF for a Submission and return its bytes inline as base64.

Args: submission_id: The identifier of the Submission.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "submission_id": "<submission_id>"
    },
    "name": "get_submission_default_pdf"
  }
}

Input Schema

NameRequiredDescriptionDefault
submission_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description must disclose behavioral traits but only mentions the download action and output format. It does not address permissions, side effects (e.g., whether downloading increments a counter), rate limits, or error conditions. The description is insufficient for full transparency.

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, consisting of a single sentence and one parameter line. It is front-loaded with the core purpose and contains no redundant 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 tool's simplicity (one parameter) and the existence of an output schema, the description covers the basic function and output format. However, it lacks critical context about usage relative to sibling tools (e.g., 'default' vs 'standard' PDF) and does not mention error handling or common use cases, making it incomplete for an agent needing to decide when to invoke it.

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 schema has only one parameter with 0% description coverage. The description adds a brief explanation ('The identifier of the Submission'), which provides minimal semantic value beyond the schema's type and title. For a single parameter, this is adequate but not exemplary.

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 action ('download') and the resource ('default Report PDF for a Submission'), and specifies the output format ('bytes inline as base64'). However, it does not differentiate from sibling tools like get_submission_report_pdf and get_submission_standard_pdf, which limits clarity on when to use this specific tool.

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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention any prerequisites, limitations, or when not to use it, leaving the AI agent without context for selection.

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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