irctc.trains.status
Get live running status of an Indian train for today or a specific date — current station, expected arrival/departure, delay in minutes, distance covered, full station-by-station schedule.
This record as markdown: /tools/io-github-whiteknightonhorse-apibase/irctc.trains.status.md
What irctc.trains.status does on Apibase
AI agents call irctc.trains.status to retrieve information from Apibase without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
start_day | integer | — | Day offset for the train journey start relative to today (0=today, 1=yesterday, 2=two days ago, up to 4). Use non-zero for multi-day trains that departed before |
train_number | string | Yes | 5-digit Indian Railways train number. Examples: '12951' (Mumbai Rajdhani Express), '12303' (Poorva Express), '22691' (Rajdhani Express Bangalore). |
Parameters from the server's own tool schema.
Why irctc.trains.status is rated Low
Tool queries live train status data with no side effects or modifications.
From the tool's definition Get live running status, current station, arrival/departure, schedule
Attacks that exploit this kind of access
The rule that runs irctc.trains.status safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Apibase, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For irctc.trains.status, this is the rule to start with:
irctc.trains.status is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Apibase, apply this rule, and every irctc.trains.status call is checked against it from then on.
Questions about irctc.trains.status
Get live running status of an Indian train for today or a specific date — current station, expected arrival/departure, delay in minutes, distance covered, full station-by-station schedule. It is categorised as a Read tool in the Apibase MCP Server, which means it retrieves data without modifying state.
irctc.trains.status accepts 2 parameters: start_day, train_number. Required: train_number. The full parameter table on this page comes from the server's own tool schema.
Register the Apibase MCP server in PolicyLayer and add a rule for irctc.trains.status: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Apibase. Nothing to install.
irctc.trains.status is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the irctc.trains.status rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for irctc.trains.status. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
irctc.trains.status is provided by the Apibase MCP server (apibase-mcp-client). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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