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Axonity Flow MCP Server

Axonity Flow MCP Server

Official
by AxonityAI
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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read_workflow_published

Retrieve the live published version of a workflow to compare with the draft and see what a pending publish would change.

Instructions

Read the LIVE published version of a workflow — what the runtime actually uses, as opposed to the draft that read_workflow returns. Diff the two to see what a pending publish would change.

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": {
      "id": "<id>"
    },
    "name": "read_workflow_published"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesThe workflow's id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description bears the full burden of behavioral disclosure. It clearly indicates the operation is read-only by using the verb 'Read' and describing the output as the 'LIVE published version'. While it does not explicitly state 'readOnly', the implication is strong and the contrast with the draft tool adds context. A small improvement would be to explicitly state it is non-destructive.

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?

Two sentences, each critical. The first defines the purpose and scope; the second adds a use case and differentiates from the sibling. No waste, front-loaded with the core action.

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?

For a simple read operation with one required parameter and no output schema, the description is complete. It explains what the tool does, why someone would use it (to see the live version and diff with draft), and how it relates to siblings. No additional context is necessary given the tool's simplicity.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning to the single parameter 'id' beyond what the schema already provides ('The workflow's id.'). The description does not elaborate on how to obtain the id or any special formatting.

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 reads the 'LIVE published version' of a workflow, using a specific verb ('Read') and resource ('workflow published'). It distinguishes itself from the sibling tool 'read_workflow' by explicitly contrasting 'published' vs 'draft'.

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 explicitly states when to use this tool (to get the live version) and what it's used for ('Diff the two to see what a pending publish would change'). It also names the alternative tool ('read_workflow') for the draft version, providing clear usage guidance.

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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