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Cta

by io.github.pipeworx-io

Cta Bus Positions

cta_bus_positions
Read-onlyIdempotent

Live Chicago CTA bus positions on a route — every vehicle currently running: lat/lon, heading, destination, delayed flag, and distance along the pattern. Answers "where is the 22 Clark bus right now" via the CTA bus tracker. Example: cta_bus_positions({ route: "22" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
routeYesBus route number, e.g. "22", "66", "146". Comma-separable up to 10.
_apiKeyNoOptional: your own CTA credentials as "train_key:bus_key" — Train Tracker key (free at transitchicago.com/developers) + Bus Tracker key (free at ctabustracker.com)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_apiKey": "your-cta-api-key",
+    "route": "22"
+  }
+]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint as false. The description adds behavioral context by specifying that it returns 'every vehicle currently running' and lists the output fields, which are not in annotations. It does not contradict annotations, but could mention rate limits or authentication requirements.

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 a single sentence with an example, front-loading the core purpose and output fields. Every word contributes to understanding, with no fluff or repetition.

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 exists, but the description compensates by listing return fields (lat/lon, heading, destination, delayed flag, distance). It is adequate for a simple tool, though it could explicitly state the response is a list of vehicles. The open-world hint is reinforced by mentioning the CTA bus tracker source.

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?

Schema coverage is 100%, with both route and _apiKey parameters described. The description provides an example call and clarifies the route parameter can be comma-separated (already in schema), adding marginal value beyond the schema. Baseline 3 is appropriate.

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 tool returns live CTA bus positions for a route, listing specific fields (lat/lon, heading, destination, delayed flag, distance). It provides a concrete example query and distinguishes it from sibling tools like cta_bus_predictions and cta_train_positions by focusing solely on bus positions.

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 implies usage when you need current positions of buses on a given route, as shown in the example. However, it does not explicitly state when to avoid it (e.g., for predictions) or name alternatives, leaving some ambiguity for the agent.

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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TDQS

A3.6/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all accept natural-language factual questions, and ask_pipeworx_beta is explicitly described as currently identical to ask_pipeworx. The entity tools (entity_profile, compare_entities, recent_changes, resolve_entity) and the many Polymarket tools also blur together, making misselection likely.

Naming Consistency3/5

Most names are snake_case and readable, with recognizable prefixes like cta_, polymarket_, and ask_pipeworx_. However, conventions are mixed: bare verbs (remember, forget, subscribe), noun-style phrases (entity_profile, bet_research), and variants like ai_visibility_check vs scan_competitor_ai_presence prevent a single predictable pattern.

Tool Count2/5

35 tools is above the comfortable range, and the count is especially mismatched for a server named 'Cta': only 4 tools actually concern Chicago transit, while the other 31 form a general-purpose research, prediction-market, and memory suite. The set feels like multiple unrelated servers merged together.

Completeness2/5

As a CTA server, the surface is notably incomplete: it has bus/train positions and predictions but lacks alerts, service disruptions, route listings, and station/stop metadata. The broader Pipeworx tools are extensive but appear bolted on, so the overall set has no coherent domain against which completeness can be judged.

Resources