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Amazon VPC Lattice MCP Server

by rlymbur

get_source_prompts

Retrieve sample prompts by specifying a source name to assist in AWS VPC Lattice networking documentation and configurations.

Instructions

Get sample prompts for a specific source

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
source_nameYesName of the source to get prompts for

Implementation Reference

  • Handler logic for the 'get_source_prompts' tool. It takes source_name from arguments, looks up the source in the sources array, and returns the source's prompts as a JSON-formatted text response. Throws error if source not found.
    case 'get_source_prompts': {
      const { source_name } = request.params.arguments as { source_name: string };
      const source = sources.find(s => s.name === source_name);
      
      if (!source) {
        throw new McpError(
          ErrorCode.InvalidParams,
          `Source not found: ${source_name}`
        );
      }
    
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(source.prompts, null, 2)
          }
        ]
      };
    }
  • Input schema definition for the 'get_source_prompts' tool, specifying that it requires a 'source_name' string parameter.
    inputSchema: {
      type: 'object',
      properties: {
        source_name: {
          type: 'string',
          description: 'Name of the source to get prompts for'
        }
      },
      required: ['source_name'],
      additionalProperties: false
    },
  • src/tools.ts:25-39 (registration)
    Tool registration entry in the exported 'tools' array, including name, description, and input schema. This array is used by the MCP server to list available tools.
    {
      name: 'get_source_prompts',
      description: 'Get sample prompts for a specific source',
      inputSchema: {
        type: 'object',
        properties: {
          source_name: {
            type: 'string',
            description: 'Name of the source to get prompts for'
          }
        },
        required: ['source_name'],
        additionalProperties: false
      },
    },
  • Supporting data file providing the 'sources' array with source names, URLs, and sample prompts used by the get_source_prompts handler.
    export const sources = [
      {
        name: 'AWS Documentation',
        url: 'https://docs.aws.amazon.com',
        prompts: [
          'What are the key features of {service}?',
          'How do I configure {service} for {use_case}?',
          'What are the best practices for using {service}?'
        ]
      },
      {
        name: 'AWS Gateway API Controller for VPC Lattice',
        url: 'https://github.com/aws/aws-application-networking-k8s',
        prompts: [
          'Does the EKS controller support {feature}',
          'Show me {type} issues in the EKS controller repo'
        ]
      },
      {
        name: 'Kubernetes Gateway API',
        url: 'https://gateway-api.sigs.k8s.io/',
        prompts: [
          'Fix error: {error_message}',
          'Best practices for {resource}'
        ]
      }
    ];
  • src/index.ts:36-38 (registration)
    MCP server request handler for listing tools, returning the 'tools' array which includes get_source_prompts.
    this.server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools,
    }));
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 what the tool does but doesn't describe behavioral traits such as whether it's read-only, if it requires authentication, rate limits, error handling, or what format the 'sample prompts' are returned in. This leaves significant gaps for a tool that likely retrieves data.

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 that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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 purpose but lacks details on usage guidelines, behavioral traits, and output format, which are important for effective tool invocation in a broader context with sibling tools.

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 'source_name' clearly documented in the schema. The description adds minimal value beyond the schema by implying the parameter is used to identify a source, but it doesn't provide additional context like valid source names or examples. This meets the baseline for high schema coverage.

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 action ('Get sample prompts') and the target resource ('for a specific source'), which provides a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'get_amazon_vpc_lattice_prompts' or 'list_sources', which appear to be related to similar domains but have different scopes or functions.

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_sources' (which might list sources before selecting one) or 'get_amazon_vpc_lattice_prompts' (which seems source-specific), leaving the agent to infer usage context without explicit direction.

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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