get_stationboardGet the live departure board for a Swiss public transport station.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of departures to return. Defaults to 10. | |
| station | Yes | Station name or ID to get the departure board for. |
| Name | Required | Description | Default |
|---|---|---|---|
| count | Yes | Number of departures returned | |
| station | Yes | Station information | |
| departures | Yes | List of departing journeys |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "count": {
+ "description": "Number of departures returned",
+ "type": "number"
+ },
+ "departures": {
+ "description": "List of departing journeys",
+ "items": {
+ "properties": {
+ "category": {
+ "description": "Transport category",
+ "type": "string"
+ },
+ "delay": {
+ "description": "Delay in minutes",
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "departure": {
+ "description": "Departure time",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "name": {
+ "description": "Journey name",
+ "type": "string"
+ },
+ "number": {
+ "description": "Vehicle number",
+ "type": "string"
+ },
+ "operator": {
+ "description": "Transport operator",
+ "type": "string"
+ },
+ "platform": {
+ "description": "Platform number",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "to": {
+ "description": "Journey destination",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "station": {
+ "description": "Station information",
+ "properties": {
+ "coordinate": {
+ "description": "Geographic coordinates",
+ "properties": {
+ "x": {
+ "description": "X coordinate (longitude)",
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "y": {
+ "description": "Y coordinate (latitude)",
+ "type": [
+ "number",
+ "null"
+ ]
+ }
+ },
+ "type": [
+ "object",
+ "null"
+ ]
+ },
+ "id": {
+ "description": "Station identifier",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "name": {
+ "description": "Station name",
+ "type": [
+ "string",
+ "null"
+ ]
+ }
+ },
+ "type": "object"
+ }
+ },
+ "required": [
+ "station",
+ "count",
+ "departures"
+ ],
+ "type": "object"
+}Input schema / examplesAdded value: +[
+ {
+ "station": "Zurich HB"
+ },
+ {
+ "limit": 15,
+ "station": "Basel SBB"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds the 'live' attribute, implying real-time data that may change between calls, but provides no further behavioral context such as rate limits or data freshness guarantees.
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?
A single, focused sentence that is front-loaded with the key verb and resource. No unnecessary words or repetition.
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?
The tool is simple with only one required parameter, full schema coverage, and an output schema. The description sufficiently covers the core purpose and context, leaving no critical gaps given the supporting metadata.
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 description coverage is 100%, with both 'station' and 'limit' fully documented in the input schema. The description itself does not add parameter-level detail, so the baseline score of 3 applies.
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 the verb ('Get'), resource ('live departure board'), and scope ('Swiss public transport station'). It distinguishes itself from siblings like 'get_connections' and 'search_stations' by focusing specifically on station departures.
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?
No guidance is provided on when to use this tool versus alternatives. There is no mention of exclusions, prerequisites, or comparison with sibling tools like 'get_connections' or 'search_stations'.
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 distinct names and purposes, but the ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) creates ambiguity as they serve overlapping needs with slight variations. Additionally, the transport tools (get_connections, get_stationboard, search_stations) are clearly distinct from the rest, but the overall set mixes domains, making it harder for an agent to know which tool to pick.
All tool names use snake_case, but there is no consistent pattern: some start with verbs (get_, list_, search_, remember, forget), some with nouns (entity_profile, recent_changes, recent_alerts), and others with adjectives (ai_visibility_check, deep_research). This inconsistency, while not chaotic, makes the set less predictable.
The server name 'swisstransport' implies a narrow Swiss transport focus, but with 34 tools, only 3 are transport-related. The count is vastly inappropriate for the suggested purpose. Even considering the actual broad domain (data query, prediction markets, memory), 34 tools is on the high side and likely overwhelming for any single server.
Inferring the domain from the tool descriptions, the set covers a wide range of capabilities: data query (ask_pipeworx, deep_research), entity comparison (compare_entities), prediction markets (polymarket_*), memory (remember/recall), subscriptions, and more. There are few obvious gaps given the scope; for example, broader financial data is accessible through ask_pipeworx. The transport subset is minimal but present.