Skip to main content
Glama
Sign In
Axonity Flow MCP Server

Axonity Flow MCP Server

Official
by AxonityAI
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

read_agent

Retrieve an agent's current draft and version by ID to obtain the version required for subsequent updates.

Instructions

Read one agent by id, including its current draft and version. Read before you update — you need the current 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": {
      "id": "<id>"
    },
    "name": "read_agent"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesThe agent's id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A4/5.0
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 of behavioral disclosure. It reveals that the tool returns the current draft and version, which is helpful, but it does not state whether the operation is read-only, required permissions, or the response format. This is adequate but not rich.

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 is two sentences with no wasted words. The first sentence states the purpose, and the second provides actionable guidance. It is appropriately front-loaded and efficient.

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 that there is no output schema, the description hints at return content ('including its current draft and version'), which is helpful but does not fully describe the response structure. For an entity tool, this is mostly complete for an AI agent to understand the use case.

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?

The single parameter 'id' has a schema description 'The agent's id.' The tool description adds no additional meaning beyond that, so it meets the baseline for 100% schema coverage without adding value.

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 'Read' and the resource 'one agent by id', and specifies what is included ('its current draft and version'). This distinguishes it from sibling tools like list_agents (which lists many) and read_agent_published (which reads only the published version).

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 explicitly advises 'Read before you update — you need the current version,' providing clear guidance on when to use this tool. It does not, however, mention when not to use it (e.g., only needing published version) or alternative tools for different contexts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools