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variflight

Variflight Tripmatch MCP Server

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by variflight

searchTrainStations

Find train stations by entering keywords like station names or locations to identify departure and arrival points for travel planning.

Instructions

Search for train stations by keyword.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesKeyword to search for train stations (e.g. 北京西)

Implementation Reference

  • dist/index.js:271-292 (registration)
    Registration of the 'searchTrainStations' MCP tool, including description, Zod input schema, and handler function that invokes the service and formats the response.
    server.tool("searchTrainStations", "Search for train stations by keyword.", {
        query: z.string().describe("Keyword to search for train stations (e.g. 北京西)"),
    }, async ({ query }) => {
        try {
            const trainStations = await flightService.searchTrainStations(query);
            return {
                content: [
                    {
                        type: "text",
                        text: JSON.stringify(trainStations, null, 2)
                    }
                ]
            };
        }
        catch (error) {
            console.error('Error searching train stations:', error);
            return {
                content: [{ type: "text", text: `Error: ${error.message}` }],
                isError: true
            };
        }
    });
  • The handler function for the searchTrainStations tool, which extracts the query, calls the OpenAlService method, and returns structured content or error response.
    server.tool("searchTrainStations", "Search for train stations by keyword.", {
        query: z.string().describe("Keyword to search for train stations (e.g. 北京西)"),
    }, async ({ query }) => {
        try {
            const trainStations = await flightService.searchTrainStations(query);
            return {
                content: [
                    {
                        type: "text",
                        text: JSON.stringify(trainStations, null, 2)
                    }
                ]
            };
        }
        catch (error) {
            console.error('Error searching train stations:', error);
            return {
                content: [{ type: "text", text: `Error: ${error.message}` }],
                isError: true
            };
        }
    });
  • Zod schema defining the input parameter 'query' as a string for the tool.
    query: z.string().describe("Keyword to search for train stations (e.g. 北京西)"),
  • Helper method in OpenAlService class that forwards the searchTrainStations request to the backend API via makeRequest.
    async searchTrainStations(query) {
        return this.makeRequest('searchTrainStations', {
            query
        });
    }
  • TypeScript declaration for the searchTrainStations method signature.
    searchTrainStations(query: string): Promise<any>;
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Search') but doesn't describe any behavioral traits such as whether it's read-only, rate-limited, requires authentication, or what the output format looks like. This is a significant gap for a tool with no annotation coverage.

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 a single, efficient sentence with no wasted words. It's front-loaded with the core purpose and appropriately sized for a simple search tool.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like safety, performance, or output format, which are crucial for an AI agent to use the tool correctly. The simplicity of the tool (one parameter) doesn't compensate for these gaps.

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 description coverage is 100%, with the single parameter 'query' fully documented in the schema. The description adds minimal value beyond the schema by mentioning 'keyword', but doesn't provide additional syntax, format details, or examples beyond what's in the schema description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Search') and resource ('train stations'), and includes the method ('by keyword'). However, it doesn't explicitly differentiate from sibling tools like 'searchTrainTickets' which searches for tickets rather than stations, though the distinction is implied.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'searchTrainTickets' or 'getFlightAndTrainTransferInfo', nor does it specify any prerequisites or exclusions for usage.

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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