bart_advisoriesCurrent BART service advisories and delays for the San Francisco Bay Area train system, plus elevator outage status at stations. Answers "is BART delayed right now", "are there BART service alerts", "which BART elevators are out". Example: bart_advisories({})
| Name | Required | Description | Default |
|---|---|---|---|
| _apiKey | No | Optional: your own BART API key (defaults to the BART public key) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {}
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds that it returns current advisories and elevator status but does not discuss data freshness, rate limits, or other behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences plus an example call, front-loaded with the main purpose, and contains no unnecessary information. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool with no required parameters and no output schema, the description adequately conveys what the tool returns. However, it could be more explicit about the output format or data structure, though the example questions hint at the response style.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single optional _apiKey parameter described in the schema. The description reinforces its optionality via the example call bart_advisories({}), but adds no new semantic details beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides current BART service advisories, delays, and elevator outage status, with example questions that distinguish it from sibling tools like bart_departures and bart_trip_planner.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives example queries indicating when to use the tool, such as asking about delays or elevator outages. It does not explicitly state when not to use it or mention alternatives, but the context from siblings is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes, but the three ask_pipeworx variants (stable, beta, grounded) overlap significantly in functionality, as do the Polymarket tools (bet_research, arbitrage, edges, etc.), which could cause an agent to misselect without careful reading of descriptions.
Naming follows multiple styles: verb_noun (ask_pipeworx, compare_entities), domain first (polymarket_arbitrage, bart_departures), and single words (remember, forget). There is no consistent pattern, making the set feel disjointed.
35 tools is on the heavy side for a single server. While each tool has a defined role, the count suggests potential for consolidation (e.g., merging ask_pipeworx variants or Polymarket tools). The server's broad scope partially justifies the count.
The tool surface covers a wide range of functionalities: structured querying, entity lookup, comparison, fact-checking, subscription management, memory, and domain-specific tools for BART and Polymarket. Minor gaps exist (e.g., no direct API for some data sources), but overall it feels comprehensive.