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BACH-AI-Tools

Flightradar24 MCP Server

get_historic_flight_events_light

Retrieve historical flight events like takeoff, landing, and gate transitions for specific flights using Flightradar24 data.

Instructions

Returns selected historical flight events (gate_departure, takeoff, cruising, airspace_transition, resuming_flightplan, descent, landed, gate_arrival), sorted by event_timestamp and grouped by flight_id. REQUIRED: flight_ids and event_types must be provided and non-empty.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
flight_idsYesComma-separated fr24_ids (maximum 15 IDs). Cannot be combined with event_datetime.
event_typesYesEvent types to filter by (comma-separated values). Available values: all, gate_departure, takeoff, cruising, airspace_transition, descent, landed, gate_arrival.

Implementation Reference

  • Core implementation of the getHistoricFlightEventsLight method, which invokes the makeRequest helper to fetch light historic flight events from the FR24 API endpoint '/historic/flight-events/light'.
    async getHistoricFlightEventsLight(params: HistoricFlightEventsQueryParams): Promise<HistoricFlightEventsLight[]> {
      return this.makeRequest<HistoricFlightEventsLight[]>('/historic/flight-events/light', params);
    }
  • Zod input schema for validating tool parameters: flight_ids (comma-separated FR24 flight IDs) and event_types.
    const historicFlightEventsSchema = z.object({
      flight_ids: z.string().min(1).describe('Comma-separated fr24_ids (maximum 15 IDs). Cannot be combined with event_datetime.'),
      event_types: z.string().min(1).describe('Event types to filter by (comma-separated values). Available values: all, gate_departure, takeoff, cruising, airspace_transition, descent, landed, gate_arrival.')
    });
  • src/server.ts:498-522 (registration)
    MCP server tool registration for 'get_historic_flight_events_light', including description, input schema reference, and the handler function that delegates to FR24Client.
    server.tool(
      'get_historic_flight_events_light',
      'Returns selected historical flight events (gate_departure, takeoff, cruising, airspace_transition, resuming_flightplan, descent, landed, gate_arrival), sorted by event_timestamp and grouped by flight_id. REQUIRED: flight_ids and event_types must be provided and non-empty.',
      historicFlightEventsSchema.shape,
      async (params: z.infer<typeof historicFlightEventsSchema>) => {
        try {
          console.log(`Raw params received by handler: ${JSON.stringify(params)}`);
          const result = await fr24Client.getHistoricFlightEventsLight(params);
          return {
            content: [{
              type: 'text' as const,
              text: `Found ${result.length} flights with historic events (light details):\n${JSON.stringify(result, null, 2)}`
            }]
          };
        } catch (error) {
          return {
            content: [{
              type: 'text' as const,
              text: `Error: ${error instanceof Error ? error.message : 'Unknown error'}`
            }],
            isError: true
          };
        }
      }
    );
  • TypeScript type definition for input parameters matching the Zod schema.
    export interface HistoricFlightEventsQueryParams {
      flight_ids: string; // Required, comma-separated fr24_ids (maximum 15 IDs)
      event_types: string; // Required, comma-separated event types or 'all'
    }
  • TypeScript type definition for the light output response structure containing flight ID, callsign, hex, and list of events.
    export interface HistoricFlightEventsLight {
      fr24_id: string;
      callsign: string;
      hex: string;
      events: FlightEvent[];
    }
Behavior3/5

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

With no annotations provided, the description carries the full burden. It describes the return format (sorted by event_timestamp, grouped by flight_id) and lists available event types, which adds value beyond the input schema. However, it doesn't disclose important behavioral traits like rate limits, authentication requirements, error handling, or what happens when invalid parameters are provided.

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 appropriately sized with two sentences that each serve a clear purpose: the first describes what the tool returns, the second states requirements. It's front-loaded with the core functionality. However, the list of event types in parentheses is somewhat verbose and could be more concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only query tool with 2 parameters and 100% schema coverage but no output schema, the description provides adequate information about what data is returned and parameter requirements. However, without annotations or output schema, it lacks details about response format, pagination, error conditions, and performance characteristics that would be helpful for an AI agent.

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 schema already documents both parameters thoroughly. The description adds minimal value beyond the schema by restating that both parameters are required and non-empty, and listing the available event types (which is also in the schema). This meets the baseline expectation when schema coverage is high.

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 verb ('Returns') and resource ('selected historical flight events'), lists specific event types, and distinguishes from sibling tools by specifying it's a 'light' version focused on events rather than positions, summaries, or counts. It provides more specificity than just restating the name.

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 provides clear context about what data is returned (events sorted by timestamp and grouped by flight_id) and includes a REQUIRED section indicating flight_ids and event_types must be provided and non-empty. However, it doesn't explicitly state when to use this tool versus alternatives like get_historic_flight_events_full or other sibling tools.

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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