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LumbreTravel MCP Server

by lumile

get_vehicle_by_name

Search for vehicles by name to retrieve a list of matching results from the travel database.

Instructions

Buscar vehículos por su nombre, retorna la lista de vehículos encontrados.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesNombre del vehículo

Implementation Reference

  • MCP tool handler implementation that executes get_vehicle_by_name by calling the ApiService method and formatting the response as MCP content.
    case 'get_vehicle_by_name': {
      const { name } = args as { name: string }
      const vehicle = await this.apiService.getVehicleByName(name)
      return {
        content: [{ type: 'text', text: JSON.stringify(vehicle, null, 2) }]
      }
    }
  • Tool definition in listTools() including name, description, and input schema requiring a 'name' string.
    {
      name: 'get_vehicle_by_name',
      description: 'Buscar vehículos por su nombre, retorna la lista de vehículos encontrados.',
      inputSchema: { type: 'object', properties: { name: { type: 'string', description: 'Nombre del vehículo' } }, required: ['name'] }
    },
  • Supporting ApiService method that performs the actual API call to retrieve vehicles by name using authenticated POST request.
    async getVehicleByName (name: string) {
      const headers = await this.getHeaders()
      const response = await fetch(`${API_CONFIG.baseUrl}/integrations/mcp/vehicle/get_vehicles_by_name`, {
        method: 'POST',
        headers: { ...headers, 'Content-Type': 'application/json' },
        body: JSON.stringify({ name })
      })
      return await this.handleResponse<any>(response)
    }
  • src/index.ts:36-48 (registration)
    Registers the MCP request handlers for listTools and callTool using the ToolsHandler instance, enabling all tools including get_vehicle_by_name.
    private setupHandlers (): void {
      // Configure handlers to list tools
      this.server.setRequestHandler(
        ListToolsRequestSchema,
        async () => this.toolsHandler.listTools()
      )
    
      // Configure handlers for tools
      this.server.setRequestHandler(
        CallToolRequestSchema,
        async (request) => await this.toolsHandler.callTool(request.params.name, request.params.arguments, this.server)
      )
    }
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 tool searches by name and returns a list, but doesn't describe key behaviors: whether it's a read-only operation (implied by 'get'), what happens if no vehicles are found (e.g., empty list or error), if it supports partial name matching, or any rate limits or authentication requirements. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 concise and front-loaded, consisting of one sentence that directly states the tool's purpose and output. There's no wasted language or redundancy. However, it could be slightly improved by structuring it to highlight key points more clearly, but it's efficient overall.

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?

Given the tool's low complexity (one parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic action and return value, but lacks details on behavioral traits (e.g., error handling) and usage context compared to siblings. For a simple read operation, it's complete enough to understand what it does, but not rich enough to guide optimal use without additional inference.

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 input schema has 100% description coverage, with the 'name' parameter documented as 'Nombre del vehículo' (name of the vehicle). The description adds no additional meaning beyond this, such as format examples (e.g., case sensitivity) or constraints (e.g., minimum length). With high schema coverage, the baseline score of 3 is appropriate, as the schema adequately defines the parameter without extra help from the 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: 'Buscar vehículos por su nombre' (search vehicles by their name) and 'retorna la lista de vehículos encontrados' (returns the list of found vehicles). It specifies the verb (search), resource (vehicles), and action (return list). However, it doesn't explicitly differentiate from sibling tools like 'list_vehicles' or 'get_agency_by_name', which follow similar patterns but for different resources.

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 'list_vehicles' (which might list all vehicles without filtering) or other 'get_by_name' tools for different resources. There's no context about prerequisites, such as needing a vehicle name to search, or limitations, like partial matches or case sensitivity.

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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