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Axonity Flow MCP Server

Axonity Flow MCP Server

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by AxonityAI
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read_prompt_snippet_version

Retrieve a specific historical version of a prompt snippet using its checkpoint number to compare versions before rolling back.

Instructions

Read one historical version of a prompt_snippet by its CHECKPOINT NUMBER (an integer like 3, from the version field in list_prompt_snippet_versions) — not by its versionId. Use it to diff two versions before rolling back.

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>",
      "version": "<version>"
    },
    "name": "read_prompt_snippet_version"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesThe prompt_snippet's id.
versionYesThe integer checkpoint number, e.g. 3.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A4.2/5.0
Behavior3/5

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 explains that the tool reads a specific version by checkpoint number and clarifies the source of the number (from list_prompt_snippet_versions). But it does not disclose any behavioral traits like authorization requirements, rate limits, or side effects, which is acceptable for a simple read operation.

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 consists of two concise sentences, with key information front-loaded. No unnecessary words or repetition.

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?

For a simple read tool with well-described parameters, the description is complete. It mentions the use case (diff/rollback) and provides necessary context. While the return format is not described, it is not critical for invoking the tool correctly given the clear purpose.

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?

The schema already describes both parameters with good coverage. The description adds value by clarifying that the version parameter is the checkpoint number (not versionId) and gives an example, as well as referencing the list_prompt_snippet_versions source. This extra context helps the agent understand the parameter semantics beyond the schema.

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 a historical version by checkpoint number, and distinguishes it from reading by versionId. The verb 'Read' and resource 'prompt_snippet_version' are specific and unambiguous.

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 a concrete use case: diffing two versions before rolling back. However, it does not explicitly compare with alternatives like read_prompt_snippet (current version) or list_prompt_snippet_versions, leaving some ambiguity about when to choose this tool over siblings.

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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