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idfm-mcp

idfm-mcp

by Drathod-24
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

next_departures

Read-only

Get real-time next departures for a Paris transit station, showing line, destination, minutes until departure, delay, and platform; optionally filter by line.

Instructions

Get the next real-time departures at a station, with minutes until departure.

Use for questions like "When is the next RER B from Gentilly?" or "Next metro at
Bastille?". Shows line, destination, minutes to wait, delay and platform.

Args:
    stop_id: Station ID from search_stop (e.g. "stop_area:IDFM:63244"). A plain
        station name also works; the best match is used.
    line: Optional line filter, e.g. "RER B", "Metro 7", "Tram T3a", "Bus 57".
        Leave empty to get all lines at the station.

Input Schema

NameRequiredDescriptionDefault
lineNo
stop_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

The description goes beyond the structured fields by explicitly listing the behavioral traits of the output: 'Shows line, destination, minutes to wait, delay and platform.' This provides valuable data context missing from the 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?

The definition is highly efficient and front-loaded, though the argument definition section is a standard listing rather than prose flow.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The definition is highly complete, detailing the expected inputs (IDs vs. names) and the specific attributes returned (line, delay, platform), making it robust for complex real-time queries.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must be comprehensive. It provides critical context that the stop_id can be a formal ID (e.g. 'stop_area:IDFM:63244') or a 'plain station name,' resolving ambiguity for the agent.

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 purpose is crystal clear, stating the tool gets 'next real-time departures at a station' and using specific questions (e.g., 'When is the next RER B?') to define its scope clearly against journey planning tools.

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?

The description provides explicit usage patterns and examples, showing agents exactly what kind of queries this tool is intended to resolve versus general travel inquiries.

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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