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kongyo2

eve-online-mcp

get-market-groups

Retrieve grouped market data for specific items and regions in EVE Online. Input a region ID and type ID to access organized market information via the MCP server.

Instructions

Get grouped market data for a region and type

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
region_idYesRegion ID to get market groups from
type_idYesItem type ID to get groups for

Implementation Reference

  • Handler function that fetches grouped market data (buy/sell statistics) from the EVE Online ESI API endpoint /markets/{region_id}/types/{type_id}/ and returns formatted JSON text response.
    async ({ region_id, type_id }) => {
      const groups = await makeESIRequest<MarketGroup>(
        `/markets/${region_id}/types/${type_id}/`
      );
    
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify({
              buy: {
                volume: groups.buy.volume,
                weighted_average: groups.buy.weighted_average,
                max: groups.buy.max,
                min: groups.buy.min,
                median: groups.buy.median
              },
              sell: {
                volume: groups.sell.volume,
                weighted_average: groups.sell.weighted_average,
                max: groups.sell.max,
                min: groups.sell.min,
                median: groups.sell.median
              }
            }, null, 2)
          }
        ]
      };
    }
  • Zod input schema defining parameters: region_id (required number) and type_id (required number).
    {
      region_id: z.number().describe("Region ID to get market groups from"),
      type_id: z.number().describe("Item type ID to get groups for"),
    },
  • src/index.ts:345-381 (registration)
    Registration of the 'get-market-groups' tool using McpServer.tool(), including description, input schema, and handler function.
    server.tool(
      "get-market-groups",
      "Get grouped market data for a region and type",
      {
        region_id: z.number().describe("Region ID to get market groups from"),
        type_id: z.number().describe("Item type ID to get groups for"),
      },
      async ({ region_id, type_id }) => {
        const groups = await makeESIRequest<MarketGroup>(
          `/markets/${region_id}/types/${type_id}/`
        );
    
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify({
                buy: {
                  volume: groups.buy.volume,
                  weighted_average: groups.buy.weighted_average,
                  max: groups.buy.max,
                  min: groups.buy.min,
                  median: groups.buy.median
                },
                sell: {
                  volume: groups.sell.volume,
                  weighted_average: groups.sell.weighted_average,
                  max: groups.sell.max,
                  min: groups.sell.min,
                  median: groups.sell.median
                }
              }, null, 2)
            }
          ]
        };
      }
    );
  • TypeScript interface defining the expected structure of market group data (buy and sell objects with volume, weighted_average, max, min, stddev, median, percentile) from ESI API.
    interface MarketGroup {
      buy: {
        volume: number;
        weighted_average: number;
        max: number;
        min: number;
        stddev: number;
        median: number;
        percentile: number;
      };
      sell: {
        volume: number;
        weighted_average: number;
        max: number;
        min: number;
        stddev: number;
        median: number;
        percentile: number;
      };
    }
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 retrieves data ('Get'), implying a read-only operation, but doesn't cover aspects like rate limits, authentication needs, error handling, or return format. This leaves significant gaps for a tool with no annotation support.

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, clearly front-loading the core purpose. It's appropriately sized for a simple tool, 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.

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 explain what 'grouped market data' entails, how results are structured, or any behavioral traits like pagination or errors. For a data retrieval tool with no structured support, more context is needed to guide the agent effectively.

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 description mentions 'region and type', aligning with the parameters 'region_id' and 'type_id' from the schema. Since schema description coverage is 100%, the schema already documents these parameters well, so the description adds minimal value beyond restating them, meeting the baseline for high 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') and resource ('grouped market data') with specific scoping parameters ('for a region and type'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get-market-history' or 'get-market-prices', which prevents a perfect score.

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?

No guidance is provided on when to use this tool versus alternatives like 'get-market-history' or 'get-market-prices'. The description implies usage for grouped data but doesn't specify scenarios, prerequisites, or exclusions, leaving the agent to infer context.

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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