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mavforge-mcp

mavforge-mcp

by msmith626
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

vehicle_info

Read-onlyIdempotent

Identify connected ArduPilot vehicles over MAVLink by reading autopilot type, firmware version and git hash, board IDs, capabilities, SITL status, and other vehicles on the link. Read-only.

Instructions

Identify the connected vehicle: autopilot, vehicle type, firmware version and git hash, board IDs, MAVLink capabilities, whether it is a simulator (SITL), and any other vehicles heard on the link. Read-only.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "vehicle_info"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
linkYes
statusYes
vehicleYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so the trailing 'Read-only' adds nothing. The one piece of genuine behavioral context beyond the annotations is that the tool reports 'any other vehicles heard on the link', revealing a broader scan scope than the name suggests; otherwise the field enumeration likely duplicates the output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is one compact sentence with the identity verb front-loaded and the returned facets following. The closing 'Read-only' is filler given the annotations, a small waste in an otherwise tight definition.

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 parameters, a present output schema, and full annotation coverage, the description only needs to orient the agent, which it does by enumerating the identity facets. The missing piece is a one-clause contrast with vehicle_status so the agent knows which sibling answers 'what is this vehicle' vs 'what is it doing now'.

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 tool takes zero parameters, so there is no parameter semantics to explain and the baseline of 4 applies. Nothing in the description misrepresents the no-argument invocation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Identify the connected vehicle') and enumerates the identity facets returned: autopilot, vehicle type, firmware/hash, board IDs, MAVLink capabilities, SITL status. It does not explicitly distinguish itself from the closest sibling, vehicle_status, leaving the agent to infer that this is static identification vs. live state.

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?

Usage is only implied by 'Identify the connected vehicle' and the presence of 'simulator (SITL)' in the content list. No sentence says when to prefer this over vehicle_status or diagnose, and no exclusions or prerequisites are given.

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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