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Axonity Flow MCP Server

Axonity Flow MCP Server

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by AxonityAI
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create_reference_doc

Create a reference document draft by submitting required fields. Validates input and returns the new document with its ID and version.

Instructions

Create a new reference_doc draft. Pass the entity's fields (camelCase) in fields; the backend validates them. Returns the created reference_doc with its id and version.

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": {
      "fields": "<fields>"
    },
    "name": "create_reference_doc"
  }
}

Input Schema

NameRequiredDescriptionDefault
fieldsYesThe reference_doc's fields as a JSON object (camelCase keys), e.g. { "name": "…", "description": "…" }.

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 provided, so the description carries full burden. It discloses that backend validates fields and returns id/version. However, it lacks details on side effects (e.g., whether draft creation is reversible), error handling, permissions, or rate limits. Adequate but minimal.

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: first declares purpose, second explains usage and output. No redundant words. Front-loaded with the action. Every sentence is essential.

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 single-parameter create tool with no output schema, the description sufficiently covers purpose, input format, and return value. It does not explain what 'draft' entails, but sibling tools for publishing suggest the lifecycle. Minor gap in not mentioning what happens on validation failure.

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 is 3. The description adds that fields must be camelCase and that backend validates them, providing extra context beyond the schema's field description. This justifies a score above baseline.

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 verb 'Create' and the resource 'reference_doc draft'. It distinguishes itself from update/read/delete siblings by specifying 'draft' and mentioning the return of id and version. No confusion with other 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 context is clear: use this to create a new reference_doc draft. It implies the fields should be provided in camelCase and validated by the backend. However, it does not explicitly exclude scenarios where this tool should not be used or mention alternatives like update or publish.

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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