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transit

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TypeScript
Hybrid

transit-mcp-server

MCP server for the 511.org SF Bay Open Data transit API. Gives an LLM live Bay Area transit data — agencies, routes, stops, real-time departures, vehicle positions and service alerts — across BART, Muni, AC Transit, Caltrain, VTA and every other 511-reporting operator.

6 tools, all read-only.

Requirements

Related MCP server: mcp-bart

Install

npm install
npm run build

Configure

{
  "mcpServers": {
    "transit": {
      "command": "node",
      "args": ["/absolute/path/to/transit-mcp-server/dist/index.js"],
      "env": { "TRANSIT_511_API_KEY": "your-token-here" }
    }
  }
}

Variable

Required

Default

Purpose

TRANSIT_511_API_KEY

yes

—

Token from https://511.org/open-data/token

TRANSIT_511_BASE_URL

no

https://api.511.org

Override the API host

TRANSIT_511_REQUEST_TIMEOUT_MS

no

30000

Per-request timeout

TRANSPORT

no

stdio

stdio or http

PORT / HOST

no

3000 / 127.0.0.1

HTTP transport bind address

MCP_PATH_SECRET

when hosted

—

Serves the endpoint at /mcp/<secret>. Required when HOST is not loopback

ALLOWED_ORIGINS

no

localhost + claude.ai

Comma-separated origin allowlist

The quota is the main constraint

511 allows 60 requests per hour per key, shared across every endpoint. That is low enough to shape how these tools should be used:

  • Resolve operator codes and stop codes once, then reuse them. They do not change.

  • Prefer transit_list_service_alerts with no operator_id — one call covers every agency.

  • Never poll transit_next_departures in a loop. Ten checks over a commute is a sixth of the hourly budget.

transit_list_operators reports how much budget is left, read from the RateLimit-Remaining header 511 returns on every response. Exceeding the quota returns 429; request an increase from transitdata@511.org.

Deploying (for Claude mobile / claude.ai connectors)

Same shape as any hosted MCP server: generate a path secret with openssl rand -hex 32, set TRANSIT_511_API_KEY and MCP_PATH_SECRET in the platform dashboard, and the included Dockerfile and railway.json work as-is on Railway, Render or Fly. The server refuses to start on a public interface without a secret. /healthz is an unauthenticated liveness probe.

Then on claude.ai in a browser: Customize → Connectors → Add custom connector, URL https://your-app.up.railway.app/mcp/<secret>.

Tools

Network — transit_list_operators, transit_list_lines, transit_find_stops

Real-time — transit_next_departures, transit_list_vehicles

Alerts — transit_list_service_alerts

Every tool takes response_format: "markdown" | "json". Markdown is the default and is optimized for an LLM reading it; JSON is the full structured payload. structuredContent is always populated regardless of format.

Examples

"When's the next N Judah?" → transit_find_stops with operator_id="SF", query="judah" to get the stop code, then transit_next_departures with that code and line="N".

"Is BART running normally?" → transit_list_service_alerts with operator_id="BA".

"Anything wrong on my commute?" → transit_list_service_alerts with no operator — one call sweeps every Bay Area agency.

"Where are the trains right now?" → transit_list_vehicles with operator_id="BA".

Design notes

Read-only by construction. 511 publishes no write endpoints, and every tool carries readOnlyHint: true. A test asserts it.

One operator_id, mapped per endpoint. 511 calls this parameter operator_id on its static endpoints and agency on its real-time ones, for the same value. Every tool here takes operator_id and the client maps it. That split is 511's problem, not the caller's.

The two real-time endpoints have genuinely different envelopes. StopMonitoring has no Siri root wrapper; VehicleMonitoring does. The published spec shows one for both — the spec is wrong, and parsing the documented shape would return nothing at all for departures. Both are parsed as the live API actually emits them, with a test pinning each.

Arrivals carry the countdown, not departures. ExpectedDepartureTime is null in essentially every real row, so keying a countdown off it would show a stop with no service. ExpectedArrivalTime is the reliable field.

A UTF-8 BOM is stripped before parsing. 511 prefixes JSON bodies with U+FEFF, which makes a naive JSON.parse throw on a perfectly valid payload. Auth failures are plain text with no BOM, so the strip happens after the status check.

Values that look like numbers and booleans often are not. Coordinates and bearings arrive as JSON strings, VehicleAtStop is the string "false", and "" is used throughout where null is meant. Coercing blindly would turn a missing position into a valid-looking 0,0 off the coast of Africa, so empty strings are treated as absent rather than zero.

The epoch-zero sentinel is not a timestamp. A trip that is scheduled but has no vehicle assigned reports RecordedAtTime of 1970-01-01T00:00:00Z. It renders as "no vehicle assigned yet" rather than "recorded 56 years ago".

GTFS-Realtime enums are decoded. 511's JSON alert rendering emits "effect": 3 where the XML rendering says SignificantDelays. Both cause and effect are mapped back to words.

511-internal pseudo-agencies are filtered out. 5E, 5F, 5O and 5S are 511 Emergency, Flap Sign, Operations and Staff — they appear in the operator list carrying no service data.

Everything is Pacific. Timestamps arrive as UTC and are rendered in America/Los_Angeles, so daylight saving is handled once here rather than by the model twice a year. Note that 511's own TimeZone field reports America/Vancouver for every Bay Area agency — a known upstream data bug, ignored deliberately.

Truncation is always stated. 511 does not paginate; it returns whole collections, and a large agency has thousands of stops. Tools take a client-side limit and every trimmed result says how much was withheld, because a silently shortened list reads as "that is everything".

Caveats

  • The hourly quota is 60 requests across all endpoints. This is the binding constraint on any workflow.

  • Operator codes are easy to guess wrong: VTA is SC (not VT), Capitol Corridor is AM (not CC), Tri Delta is 3D. transit_list_operators prints these traps in its output.

  • Stop codes belong to one operator and are not interchangeable between agencies.

  • transit_find_stops filters on this server, so a narrow query does not save quota — the full stop list is fetched either way.

  • Real-time predictions extend roughly 90 minutes ahead, and 511 omits a route's final arrival-only stop from the departures feed.

  • tripupdates and vehiclepositions are protobuf-only with no JSON option, so they are deliberately not exposed — supporting them would mean taking on a protobuf dependency for data the SIRI endpoints already cover.

Project layout

src/
├── index.ts               # entry point, transport selection
├── constants.ts           # enums, limits, operator-code traps
├── types.ts               # interfaces for every 511 entity
├── services/
│   └── transit-client.ts  # fetch wrapper, auth, BOM stripping, quota tracking, errors
├── schemas/
│   ├── inputs.ts          # Zod input schemas
│   └── outputs.ts         # structuredContent schemas
├── formatters/
│   ├── response.ts        # limiting, truncation, Pacific-time rendering
│   └── entities.ts        # per-entity markdown rendering
└── tools/
    ├── network.ts         # operators, lines, stops
    ├── departures.ts      # real-time arrivals and vehicles
    └── alerts.ts          # service alerts

Tests

npm run build
npm test            # 42 checks: handshake, BOM, envelopes, quirks, errors (mocked API)
npm run test:http   # 17 checks: config validation, path-secret gating, method handling, origins

Both suites run against a local mock that deliberately reproduces 511's real quirks — the BOM, the missing Siri wrapper, stringified booleans and coordinates, the epoch sentinel, and plain-text error bodies — because those are exactly what a naive client gets wrong.

Available Tools

6 tools
transit_find_stopsFind Transit StopsA
Read-onlyIdempotent

Find an agency's stops by name, and get the stop codes the real-time tools need.

This is the bridge between "Downtown Berkeley" and the code transit_next_departures wants. Pass a query: a large agency has thousands of stops, and 511 returns all of them in one unpaginated response.

Args:

  • operator_id (string): agency code from transit_list_operators

  • query (string): substring match on the stop name — strongly recommended

  • limit (number): maximum stops to return (default: 25)

  • response_format ('markdown' | 'json'): output format (default: 'markdown')

Returns: { "count": number, "total": number, "truncated": boolean, "stops": [ { "id": string, "Name": string, "Location": { "Latitude": string, "Longitude": string } } ] }

Examples:

  • "When's the next train from Downtown Berkeley?" -> operator_id='BA', query='downtown berkeley', then pass the id to transit_next_departures

  • "Find Muni stops on Judah" -> operator_id='SF', query='judah'

  • Don't use when: you already have the stop code

Error Handling:

  • Stop codes belong to ONE operator and are not interchangeable between agencies

  • Filtering happens on this server, so a narrow query does not save quota — the full list is fetched either way

  • 511 allows 60 requests per hour across ALL endpoints

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum results to return (max 200)
queryNoCase-insensitive substring match on the stop name. Strongly recommended — a large agency has thousands of stops
operator_idYesOperator code from transit_list_operators, e.g. 'BA' for BART, 'SF' for Muni
response_formatNoOutput format: 'markdown' for human-readable, 'json' for machine-readablemarkdown

Output Schema

ParametersJSON Schema
NameRequiredDescription
countYes
stopsYes
totalYes
truncatedYes

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds meaningful behavior: server-side filtering (no quota savings), unpaginated response from 511, and the 60-request/hour rate limit. It also clarifies that stop codes are operator-specific—valuable context beyond the annotations.

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 longer but well-structured with clear sections (Args, Returns, Examples, Error Handling). Each section contributes distinct value: the main purpose is front-loaded, examples are concise, and error handling is pertinent. No fluff or redundancy.

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 description is fully self-contained: it includes the return object structure, examples mapping to actual operator IDs, error-handling notes, rate limits, and the relationship to sibling tools. With an output schema present and annotations covering safety, nothing an agent needs to invoke correctly is missing.

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 description coverage is 100%, so the baseline is 3. The description's Args section largely repeats schema descriptions (e.g., 'operator_id' from transit_list_operators, 'query' substring match and 'strongly recommended'). It adds no new per-parameter semantics; the 'strongly recommended' phrasing already appears in the schema. The unpaginated response note is behavioral, not parameter-specific.

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 identifies the tool's purpose: 'Find an agency's stops by name, and get the stop codes the real-time tools need.' It explicitly ties the tool to transit_next_departures, distinguishing it from other transitive tools. The purpose is specific and actionable.

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 context: 'This is the bridge between "Downtown Berkeley" and the code transit_next_departures wants.' It also states a clear when-not: 'Don't use when: you already have the stop code.' Examples illustrate typical queries, making the intended conditions unambiguous.

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

transit_list_linesList Transit LinesA
Read-onlyIdempotent

List an agency's routes.

Use this to resolve a line name a user mentions into the id the real-time tools filter on, or to answer "what routes does this agency run".

Args:

  • operator_id (string): agency code from transit_list_operators

  • query (string): substring match on the line name or public code

  • limit (number): maximum lines to return (default: 25)

  • response_format ('markdown' | 'json'): output format (default: 'markdown')

Returns: { "count": number, "total": number, "truncated": boolean, "lines": [ { "Id": string, "Name": string, "PublicCode": string, "TransportMode": string, "Monitored": boolean } ] }

Examples:

  • "What BART lines are there?" -> operator_id='BA'

  • "Is there an N line on Muni?" -> operator_id='SF', query='N'

  • Don't use when: you want stops on a line (use transit_find_stops)

Error Handling:

  • A large agency returns many lines; use query to narrow rather than raising limit

  • 511 allows 60 requests per hour across ALL endpoints

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum results to return (max 200)
queryNoCase-insensitive substring match on the line name or public code
operator_idYesOperator code from transit_list_operators, e.g. 'BA' for BART, 'SF' for Muni
response_formatNoOutput format: 'markdown' for human-readable, 'json' for machine-readablemarkdown

Output Schema

ParametersJSON Schema
NameRequiredDescription
countYes
linesYes
totalYes
truncatedYes

TDQS

A4.7/5.0
Behavior5/5

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

The annotations already declare readOnly, idempotent, and non-destructive hints. The description goes further by disclosing the response shape, the truncation flag, the possibility of many results for large agencies, and the 60-request-per-hour rate limit across all endpoints. This adds behavioral context beyond the annotations and contradicts nothing.

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 well-organized with clear sections (Summary, Args, Returns, Examples, Error Handling). It front-loads the purpose and usage, and every sentence adds value—examples, exclusions, rate limits, and return format. Despite covering many aspects, it remains concise and skimmable.

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 tool has 4 parameters, an output schema, and sits among 5 siblings. The description covers all essentials: purpose, parameter examples, return structure, error handling, and even the rate limit. There is nothing an agent needs to know to call this correctly that is missing, and the output schema already documents the return shape.

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?

The schema covers all parameters with detailed descriptions (100% coverage), so the description does not need to duplicate that. It adds a few examples (operator_id='BA', 'SF') and clarifies that query is a case-insensitive substring, but these are minor enhancements. The baseline of 3 is appropriate because the schema already carries the main semantic load.

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 states a specific verb ('List') and resource ('an agency's routes'), and immediately explains its practical use (resolving a line name into an id, answering route questions). It explicitly distinguishes itself from a sibling tool ('Don't use when: you want stops on a line (use transit_find_stops)'), which is a clear differentiation.

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?

It gives explicit 'Use this to...' guidance and an explicit 'Don't use when...' with a named alternative. Examples illustrate common queries, and the error handling section advises when to prefer query narrowing over raising limit. This leaves no ambiguity about when to invoke this tool.

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

transit_list_operatorsList Transit OperatorsA
Read-onlyIdempotent

List Bay Area transit agencies and their operator codes.

Start here. Every other tool needs an operator code, and this is what produces them — BART is 'BA', Muni is 'SF', AC Transit is 'AC', Caltrain is 'CT'.

The Monitored flag matters: agencies reporting real-time data support live departures and vehicle positions, while schedule-only agencies do not.

Args:

  • monitored_only (boolean): only agencies publishing real-time data (default: false)

  • limit (number): maximum operators to return (default: 50)

  • response_format ('markdown' | 'json'): output format (default: 'markdown')

Returns: { "count": number, "total": number, "truncated": boolean, "operators": [ { "Id": string, "Name": string, "Monitored": boolean, "PrimaryMode": string, "TimeZone": string } ] }

Examples:

  • "What transit agencies are there?" -> call with no arguments

  • "Which ones have live tracking?" -> monitored_only=true

  • Call this first whenever the user names an agency, to resolve its code

Error Handling:

  • Ignore the TimeZone field: 511 reports "America/Vancouver" for every Bay Area agency, which is a known upstream data bug. Everything here is Pacific time

  • 511-internal pseudo-agencies (5E, 5F, 5O, 5S) are filtered out — they carry no service data

  • 511 allows 60 requests per hour across ALL endpoints, so cache this rather than re-fetching

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum results to return (max 200)
monitored_onlyNoOnly agencies that publish real-time data, excluding schedule-only ones
response_formatNoOutput format: 'markdown' for human-readable, 'json' for machine-readablemarkdown

Output Schema

ParametersJSON Schema
NameRequiredDescription
countYes
totalYes
operatorsYes
truncatedYes

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds substantial behavioral context beyond those: the Monitored flag semantics, the known TimeZone bug (inaccurate 'America/Vancouver' values), the filtering of pseudo-agencies (5E, 5F, 5O, 5S), and the rate limit (60 req/hour across all endpoints) with caching advice. This is exactly the kind of operational detail an agent needs and the annotations do not provide.

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 thorough but efficiently organized into clear sections (Args, Returns, Examples, Error Handling). Every sentence adds value: the opening line is the purpose, the 'Start here' directive is front-loaded, examples are concise, and error handling covers real-world quirks. No redundancy or filler—each element earns its place.

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?

For a tool with 3 optional parameters and an output schema, the description covers everything needed to call it correctly: it provides default values, return shape (matching the output schema), examples, and critical edge cases (TimeZone bug, filtering, rate limit). Even though the output schema exists, the description's inclusion of the return shape is redundant but not harmful; the error-handling notes are essential and not available anywhere else. The description is fully sufficient for an agent to use this tool without surprises.

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?

Schema coverage is 100%, so baseline is 3. The description goes beyond the schema by explaining the semantic impact of monitored_only (supports live departures/vehicle positions vs schedule-only), giving concrete usage examples for each parameter, and clarifying the response_format default. It also mentions the default for limit in prose. While the schema already has descriptions, the description adds contextual meaning that helps an agent decide parameter values appropriately.

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 opens with a clear verb-resource pair: "List Bay Area transit agencies and their operator codes." It immediately differentiates from siblings by noting "Every other tool needs an operator code, and this is what produces them," which is unique among the sibling tools. The specific examples (BART='BA', Muni='SF') further cement the purpose.

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 instructs when to use: "Start here." and "Call this first whenever the user names an agency, to resolve its code." It also explains the monitored_only flag's relevance for choosing between live vs schedule-only agencies, effectively guiding the agent on when to apply different parameter values. No alternatives are named, but the tool is clearly positioned as the entry point, so exclusion guidance is unnecessary.

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

transit_list_service_alertsList Transit Service AlertsA
Read-onlyIdempotent

Service alerts — delays, outages, detours and planned disruptions.

Answers "is BART running normally", "why is my line delayed" and "anything I should know before I leave". Omit operator_id to sweep every Bay Area agency in a single request, which is also the kinder option against the hourly quota.

Args:

  • operator_id (string): limit to one agency; omit for all operators

  • query (string): substring match on the headline or description

  • active_only (boolean): only alerts whose active period covers now (default: true)

  • limit (number): maximum alerts to return (default: 25)

  • response_format ('markdown' | 'json'): output format (default: 'markdown')

Returns: { "count": number, "total": number, "truncated": boolean, "alerts": [ { "id": string, "header": string, "description": string, "effect": string, "cause": string, "routes": [string], "start": number, "end": number } ] // epoch SECONDS }

Examples:

  • "Any BART delays?" -> operator_id='BA'

  • "Anything wrong on my commute?" -> omit operator_id, read across agencies

  • "Weekend track work?" -> active_only=false, query='weekend'

  • Don't use when: you want a specific stop's arrivals (use transit_next_departures)

Error Handling:

  • No alerts is genuinely good news, not an error — it means normal service

  • Timestamps here are epoch seconds, unlike the ISO strings elsewhere in this API

  • Setting active_only=false surfaces future planned work as well as current problems

  • 511 allows 60 requests per hour across ALL endpoints

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum results to return (max 200)
queryNoCase-insensitive substring match on the alert headline or description
active_onlyNoOnly alerts whose active period covers now
operator_idNoLimit to one agency; omit for alerts across every Bay Area operator
response_formatNoOutput format: 'markdown' for human-readable, 'json' for machine-readablemarkdown

Output Schema

ParametersJSON Schema
NameRequiredDescription
countYes
totalYes
alertsYes
truncatedYes

TDQS

A5/5.0
Behavior5/5

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

Annotations only indicate read-only, idempotent, and non-destructive behavior. The description adds crucial behavioral nuance: no alerts means normal service (not an error), timestamps are epoch seconds unlike the ISO strings in other API endpoints, active_only=false surfaces future planned work, and rate limits. This goes well beyond the annotations.

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?

Structured with Args, Returns, Examples, and Error Handling sections. The purpose and primary use cases are front-loaded in the first sentence, and every sentence adds value—examples, rate limits, or format distinctions. No redundancy or fluff.

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 output schema is present and the description includes a return format example with field types. It covers error handling (no alerts ≠ error), rate limits, timestamp format, and sibling routing. For a 5-parameter tool with no required parameters, this is fully complete for an agent.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds substantial meaning: operator_id omission sweeps all agencies and is 'kinder' against quota, active_only=false is tied to 'weekend track work' examples, and query is illustrated with a practical use case. These contextual insights help an agent choose parameter values effectively.

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 states a specific verb ('List') and resource ('Transit Service Alerts'), and grounds it with concrete questions it answers ('is BART running normally', 'why is my line delayed'). It explicitly differentiates from the sibling transit_next_departures by naming when not to use it, making the purpose unmistakable.

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 the tool (answering delay/outage questions) and when not to ('Don't use when: you want a specific stop's arrivals (use transit_next_departures)'). Also gives operational guidance, such as omitting operator_id to sweep all agencies and conserve quota—practical context an agent needs.

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

transit_list_vehiclesList Transit Vehicle PositionsA
Read-onlyIdempotent

Live positions of an agency's vehicles currently in service.

Answers "where are the trains right now" and "how many buses are running on this line". For "when does one get to me", use transit_next_departures instead.

Args:

  • operator_id (string): agency code from transit_list_operators

  • line (string): only vehicles on this line, matched on name or id

  • limit (number): maximum vehicles to return (default: 25)

  • response_format ('markdown' | 'json'): output format (default: 'markdown')

Returns: { "count": number, "total": number, "truncated": boolean, "vehicles": [ { "line": string, "vehicle": string, "destination": string, "latitude": number | null, "longitude": number | null, "bearing": number | null, "recorded_at": string } ] }

Examples:

  • "How many Muni trains are running on the N?" -> operator_id='SF', line='N'

  • "Where are the BART trains?" -> operator_id='BA'

  • Don't use when: you want arrival times at a stop (use transit_next_departures)

Error Handling:

  • Coordinates arrive as strings and may be empty; those vehicles report "position unavailable" rather than a false 0,0

  • An agency with no real-time feed returns nothing — check Monitored in transit_list_operators

  • 511 allows 60 requests per hour across ALL endpoints

ParametersJSON Schema
NameRequiredDescriptionDefault
lineNoOnly vehicles on this line
limitNoMaximum results to return (max 200)
operator_idYesOperator code from transit_list_operators, e.g. 'BA' for BART, 'SF' for Muni
response_formatNoOutput format: 'markdown' for human-readable, 'json' for machine-readablemarkdown

Output Schema

ParametersJSON Schema
NameRequiredDescription
countYes
totalYes
vehiclesYes
truncatedYes

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already signal read-only, idempotent, and open-world behavior. The description adds valuable, non-obvious behavioral details: coordinates arrive as strings and may be empty, agencies with no real-time feed return nothing (with a pointer to check 'Monitored'), and a 60-requests-per-hour rate limit. This goes well beyond the annotations and prepares the agent for realistic edge cases.

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 description is longer than strictly necessary because it repeats the Args and Returns sections that already exist in the schema. However, it is well-structured with clear sections (purpose, args, returns, examples, error handling) and the most important guidance (purpose and alternative) is front-loaded. Every section adds unique value (examples, error handling, rate limits), so the length is justified despite some redundancy.

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?

For a list tool with an output schema and read-only annotations, the description covers all essential context: proper use cases, alternatives, parameter semantics, edge cases (missing coordinates, empty feeds, rate limits), and concrete examples. Nothing an agent needs to call it correctly is missing.

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?

Schema coverage is 100%, so the schema fully documents each parameter. The description adds some meaning beyond that: it clarifies that 'line' matches on name or id, and provides concrete examples (operator_id='SF', line='N') that illustrate how parameters map to real queries. Defaults for limit and response_format are repeated, but the examples and matching detail provide modest added value.

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 opens with a clear, specific statement of what the tool does: 'Live positions of an agency's vehicles currently in service.' It names the resource (vehicles) and action (list positions), and explicitly differentiates from a sibling tool ('For "when does one get to me", use transit_next_departures instead'), so an agent can distinguish it without opening schemas.

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?

Provides explicit when-to-use guidance: answers 'where are the trains right now' and 'how many buses are running on this line', and gives a direct exclusion: 'Don't use when: you want arrival times at a stop' with the alternative named. Examples reinforce correct usage and operator/line selection.

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

transit_next_departuresNext Transit DeparturesA
Read-onlyIdempotent

Live arrival predictions for the next vehicles at a stop.

This is the tool for "when is my next train/bus". It returns real-time predictions, not the printed timetable, and reports minutes-from-now alongside Pacific clock time.

Args:

  • operator_id (string): agency code from transit_list_operators, e.g. 'BA', 'SF'

  • stop_code (string): stop code from transit_find_stops. Codes belong to ONE operator and are not interchangeable between agencies

  • line (string): only departures on this line, matched on name or id

  • limit (number): maximum departures to return (default: 10)

  • response_format ('markdown' | 'json'): output format (default: 'markdown')

Returns: { "count": number, "total": number, "truncated": boolean, "operator": string, "stop_code": string, "stop_name": string, "retrieved_at": string, "departures": [ { "line": string, "destination": string, "expected": string, "aimed": string, "minutes": number, "vehicle": string | null, "at_stop": boolean } ] }

Examples:

  • "When's the next N Judah?" -> operator_id='SF', stop_code from transit_find_stops, line='N'

  • "Next BART from Downtown Berkeley?" -> operator_id='BA', the stop's code

  • Don't use when: you want the scheduled timetable rather than live predictions

Error Handling:

  • An empty result usually means service has ended for the night, or the stop is a route's final stop — 511 omits arrival-only terminals from this feed

  • Predictions extend roughly 90 minutes ahead; nothing beyond that appears

  • Rows reading "scheduled only, no live prediction" have no vehicle assigned yet

  • 511 allows 60 requests per hour across ALL endpoints — never poll this in a loop

ParametersJSON Schema
NameRequiredDescriptionDefault
lineNoOnly departures on this line, matched against the line name or id
limitNoMaximum results to return (max 200)
stop_codeYesStop code from transit_find_stops. Codes are specific to one operator
operator_idYesOperator code from transit_list_operators, e.g. 'BA' for BART, 'SF' for Muni
response_formatNoOutput format: 'markdown' for human-readable, 'json' for machine-readablemarkdown

Output Schema

ParametersJSON Schema
NameRequiredDescription
countYes
totalYes
operatorNo
stop_codeNo
stop_nameNo
truncatedYes
departuresYes
retrieved_atNo

TDQS

A5/5.0
Behavior5/5

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

Annotations already declare readOnly, idempotent, and non-destructive hints. The description adds substantial behavioral context: real-time vs static, minutes-from-now plus Pacific clock time, 'scheduled only' rows, a 90-minute prediction horizon, empty results meaning (end of service or arrival-only terminal), and a 60-requests-per-hour rate limit. This goes far beyond the annotations, providing critical operational details an agent needs to interpret results and avoid misuse.

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?

Structured with clear sections (Purpose, Args, Returns, Examples, Error Handling) and front-loaded with the core purpose. Every sentence adds value; error handling is critical for correct agent behavior. It is detailed but not flabby — the length is justified by the operational caveats and edge cases.

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?

For a tool with 5 parameters and an output schema, the description covers all essential usage aspects: parameter semantics, error scenarios (empty results, truncated predictions), time horizon, rate limits, and a full output structure in the Returns section. Even though an output schema is provided, the description's explicit sample JSON and explanation of fields further aid the agent. Nothing needed for correct invocation is missing.

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?

Even though schema coverage is 100%, the description enriches every parameter: it provides real examples (operator_id 'BA'/'SF', stop_code from transit_find_stops), warns that stop codes are operator-specific and not interchangeable, clarifies line matching ('matched on name or id'), and explains response_format options. The Args section adds value beyond the schema's terse descriptions, especially for stop_code and line.

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?

Description states a specific verb and resource: 'Live arrival predictions for the next vehicles at a stop' and explicitly positions it as 'the tool for when is my next train/bus'. It distinguishes from the printed timetable and clarifies scope (real-time, not static), making it clearly different from sibling tools that list operators, stops, lines, vehicles, or alerts.

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?

Provides explicit when-to-use guidance via examples ('When's the next N Judah?' maps to specific parameters), an explicit 'Don't use when' exclusion for scheduled timetable, and references prerequisite tools (transit_list_operators, transit_find_stops) for parameter sourcing. It also includes rate-limit guidance ('never poll this in a loop'), which is directly relevant to usage.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 6 tool updatesv1.0.0
    • First observedtransit_find_stops
    • First observedtransit_list_lines
    • First observedtransit_list_operators
    • First observedtransit_list_service_alerts
    • First observedtransit_list_vehicles
    • First observedtransit_next_departures
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TDQS

A4.8/5.0
Disambiguation5/5

Each tool targets a distinct resource: operators, lines, stops, departures, vehicles, and alerts. Descriptions explicitly cross-reference when to use which (e.g., 'Don't use when' sections), eliminating ambiguity. No two tools overlap in purpose.

Naming Consistency5/5

All tools share the 'transit_' prefix and follow a consistent verb-object pattern: list_operators, list_lines, find_stops, next_departures, list_vehicles, list_service_alerts. Minor variation between 'list', 'find', and 'next' but the style is uniform and predictable.

Tool Count5/5

Six tools are well-scoped for a transit information server, covering discovery (operators, lines, stops), real-time queries (departures, vehicles), and alerts. No tool is redundant, and the count feels neither sparse nor bloated.

Completeness4/5

The tool surface covers the full workflow of querying transit info: discover agencies, lines, stops, then get live departures, vehicle positions, and alerts. A minor gap is the lack of a dedicated scheduled timetable tool, though the departures endpoint includes aimed times. Overall, the domain is well covered.

Maintenance

ActivityMaintained
ResponsivenessNo issues

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