MBTA MCP Server

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mbta_get_predictions_for_stop

Retrieve real-time transit predictions for any MBTA stop by stop ID, with optional filters for route, direction, and result limit.

Instructions

Get all predictions for a specific stop.

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": {
      "stop_id": "<stop_id>"
    },
    "name": "mbta_get_predictions_for_stop"
  }
}

Input Schema

Name	Required	Description
`stop_id`	Yes	Stop ID to get predictions for
`route_id`	No	Filter by specific route
`direction_id`	No	Filter by direction (0 or 1)
`page_limit`	No	Number of results to return (default: 10)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0May 26, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations exist, so the description must fully disclose behavior. It only says 'Get all predictions' without specifying time horizon (real-time vs future), data freshness, error handling for invalid stop IDs, or any rate limits. This is insufficient for a tool with no annotations.

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?

One sentence, no fluff. However, it could be slightly expanded without sacrificing conciseness. Still efficient.

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

Completeness2/5

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

No output schema exists, and the description does not explain what the predictions contain (e.g., arrival/departure times, vehicles, status). This leaves the agent guessing about the return structure.

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?

Input schema covers all 4 parameters with descriptions (100% coverage). Description adds no extra meaning beyond schema; it just reiterates 'for a specific stop' which matches stop_id. Baseline of 3 is appropriate.

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?

Description clearly states 'Get all predictions for a specific stop,' but does not differentiate from the sibling 'mbta_get_predictions' which might also return predictions. The name itself implies the scope, but the description could explicitly mention that this tool is scoped to a single stop.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives like mbta_get_predictions, mbta_get_chained_track_predictions, or mbta_get_prediction_stats. No when-not-to-use or context provided.

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