Skip to main content
Glama

find_locomotive

Resolve a locomotive's name to its DCC address for throttle control. Accepts partial and case-insensitive names, clarifying when multiple matches occur.

Instructions

Resolve a locomotive's spoken/typed name to its DCC address.

Use this whenever the user names a locomotive ("the Autorail", "141R", "start the Pacific") instead of giving a DCC address directly — call this first to get the address, then pass that address to acquire_throttle/set_speed/set_direction/set_function/ lights_on/lights_off/etc.

Matching is tolerant: case-insensitive, accent-insensitive (useful for French names — "boite a sel" matches "Boite à Sel"), and accepts an exact name or an unambiguous partial match ("autorail" matches "Autorail"). If the name matches more than one roster entry, or matches none, this returns an "error" explaining why (listing the candidates or the full roster) instead of guessing — ask the user to clarify rather than picking one yourself.

Includes the same "dcc_system"/"dcc_system_name"/"max_speed_percent" fields as list_roster — see that tool's docstring for what they mean.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
Behavior4/5

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

No annotations, so description covers behavior: case-insensitive, accent-insensitive matching, exact/partial, error handling on no/match ambiguity. Mentions it includes fields from list_roster. Lacks mention of performance or side effects, but none expected.

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?

Concise and well-structured: opens with purpose, then usage context, then detailed behavior. No wasted words; 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?

No output schema, but description explains it returns address on success and error details on failure. Mentions it has same fields as list_roster. Could be clearer on exact output structure, but sufficient for a lookup tool.

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?

Single parameter 'name' with 0% schema coverage. Description clarifies it's the spoken/typed name, explains matching tolerance, and indicates it resolves to address. This compensates well for lack of schema description.

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?

Clear verb 'resolve' and resource 'locomotive name to DCC address', distinct from sibling tools like acquire_throttle or set_speed which use the address.

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

Usage Guidelines5/5

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

Explicitly states when to use: when user names a locomotive instead of providing address. Directs to call this first, then pass address to other tools. Also explains behavior on ambiguous/non-matches: return error without guessing.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/HO44-PROJECT/MrJ-JMRI-MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server