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tensorart-mcp

tensorart-mcp

by giacomodiguida
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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run_workflow_template

Executes a saved Tensor.Art workflow template with specified node field values, enabling reproducible image generation and ComfyUI workflow runs without rebuilding the graph.

Instructions

Run a saved Tensor.Art workflow template. fields: [{"nodeId": "27", "fieldName": "text", "fieldValue": "..."}].

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": {
      "template_id": "<template_id>",
      "fields": "<fields>"
    },
    "name": "run_workflow_template"
  }
}

Input Schema

NameRequiredDescriptionDefault
waitNo
fieldsYes
template_idYes
timeout_secNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
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 behavioral burden. It states that a workflow is run but does not disclose side effects, whether execution is synchronous, how wait/timeout behave, credit usage, or what is returned.

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 definition is short and front-loaded with the core action. The fields example is useful, though the prose is slightly stripped down and could more clearly separate parameter guidance.

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?

For a four-parameter execution tool with no annotations and no output schema, the description is incomplete. It does not explain wait behavior, timeout semantics, required template_id meaning, or the result/job outcome an agent should expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must explain all four parameters. It only gives a partial example for fields and leaves template_id, wait, and timeout_sec undocumented, so it does not compensate for the coverage gap.

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?

States a specific verb and resource: "Run a saved Tensor.Art workflow template." The purpose is clear, but it does not distinguish this tool from the sibling run_workflow, so it falls short of a 5.

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?

Provides no guidance on when to use this tool rather than run_workflow or run_workflow_template alternatives. It also omits prerequisites, expected context, and when-not-to-use conditions.

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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