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Axonity Flow MCP Server

Axonity Flow MCP Server

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by AxonityAI
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restore_output_schema_version

Restore an output schema draft to a prior version. The current draft is snapshotted before rollback, leaving the live version unchanged.

Instructions

Roll a output_schema's DRAFT back to an earlier version. Takes the versionId (a UUID from list_output_schema_versions), NOT the checkpoint number. The current draft is snapshotted first, so this is itself undoable. It changes only the draft — what is live stays live until a human approves a new publish.

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>",
      "versionId": "<versionId>",
      "expectedVersion": "<expectedVersion>"
    },
    "name": "restore_output_schema_version"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesThe output_schema's id.
versionIdYesThe version row's UUID.
expectedVersionYesThe draft version you last read — 409 if stale.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description fully discloses that the current draft is snapshotted before rollback, making the operation undoable, and that it only affects the draft, not live. This is comprehensive.

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?

Three sentences, front-loaded with purpose, no wasted words. Efficiently conveys key nuances.

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 tool with 3 required parameters and no output schema, the description covers all needed context: operation, snapshot undo, draft-only effect, and parameter sourcing. Complete for agent decision-making.

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

Parameters4/5

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

Schema coverage is 100%, so baseline 3. Description adds value by clarifying that versionId is a UUID from list_output_schema_versions and that expectedVersion is for staleness detection, going beyond schema descriptions.

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 action ('Roll a output_schema's DRAFT back to an earlier version') and specifies the resource. It distinguishes from siblings like restore_output_schema and list_output_schema_versions by focusing on draft rollback and clarifying the versionId parameter.

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

Usage Guidelines4/5

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

The description provides explicit guidance on when to use (to roll back draft) and what not to do (use versionId, not checkpoint number). It mentions the snapshot behavior making it undoable, but could further contrast with publishing tools.

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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