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Axonity Flow MCP Server

Axonity Flow MCP Server

Official
by AxonityAI
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TypeScript
Local

create_agent

Create a new agent draft by passing its fields in camelCase; the backend validates and returns the agent with id and version.

Instructions

Create a new agent draft. Pass the entity's fields (camelCase) in fields; the backend validates them. Returns the created agent 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_agent"
  }
}

Input Schema

NameRequiredDescriptionDefault
fieldsYesThe agent'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

A4/5.0
Behavior4/5

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

Discloses that backend validates fields and returns id/version. No annotations exist, so description carries burden. Missing details on permissions or side effects but adequate for a creation tool.

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, no fluff. Front-loaded with action and resource. Every sentence adds value.

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?

With no output schema, includes return structure. Mentions draft status. Missing error/validation details but sufficient for typical use.

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 already describes fields as JSON with camelCase. Description adds validation note but doesn't significantly extend meaning beyond 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?

Clearly states it creates a new agent draft, distinguishing from update/delete/publish siblings. Returns id and version, reinforcing the action.

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

Usage Guidelines3/5

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

Does not explicitly specify when to use vs alternatives like update_agent or request_publish_agent. The purpose is implicit but lacks direct 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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