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Axonity Flow MCP Server

Axonity Flow MCP Server

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by AxonityAI
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restore_deleted_reference_doc_version

Restore a previously deleted reference document version back into history without altering the current draft. Use list_deleted_reference_doc_versions to find the version UUID.

Instructions

Undo delete_reference_doc_version — bring a removed version row back into history. This does NOT change the current draft (unlike restore_reference_doc_version); it only makes the row visible/restorable again. Takes no version check.

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>"
    },
    "name": "restore_deleted_reference_doc_version"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesThe reference_doc's id.
versionIdYesThe version row's UUID, from list_deleted_reference_doc_versions.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool does NOT change the current draft, only makes the row visible/restorable, and requires no version check. This is good behavioral context for a restore operation, though more details about potential error states could be added.

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, front-loaded with purpose. Every sentence adds value—purpose, distinction, and behavioral note. No unnecessary words.

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 no output schema and simple parameters, the description covers the essential behavior. It explains the effect and the difference from a sibling tool. However, it could mention what happens if the version is already restored or if parameters are invalid, but not a major gap.

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 coverage is 100%, so baseline is 3. The description adds minor context: the versionId comes from list_deleted_reference_doc_versions, which is helpful but not deep. No additional semantics beyond what the schema provides.

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?

Description starts with 'Undo delete_reference_doc_version — bring a removed version row back into history,' clearly stating the action and resource. It explicitly distinguishes from restore_reference_doc_version by noting it does not change the current draft, which helps the agent differentiate among sibling tools.

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 explains when to use (undo delete without affecting draft) and contrasts with a related tool. It also mentions 'Takes no version check,' providing implicit guidance. However, it does not explicitly state when not to use or list alternative scenarios, so it's slightly less than perfect.

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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