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blake365

Macrostrat MCP Server

by blake365

Find Columns

find-columns

Retrieve geological stratigraphic columns and rock layer data for specific coordinates to analyze bedrock formations and geological history.

Instructions

Find geological stratigraphic columns, rock layers, and geological history for any location worldwide. Use for geology, bedrock, formations, age dating, and stratigraphic analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesA valid latitude in decimal degrees
lngYesA valid longitude in decimal degrees
adjacentsNoInclude adjacent columns
responseTypeNoThe length of response long or shortlong

Implementation Reference

  • The handler function that executes the tool logic: destructures input parameters, builds query params, fetches data from Macrostrat columns API endpoint, and returns the JSON response as text content.
    async (request) => {
      const { lat, lng, adjacents, responseType } = request;
      const params = new URLSearchParams({
        lat: lat.toString(),
        lng: lng.toString(),
        adjacents: adjacents?.toString() ?? "false",
        response: responseType,
      });
      const response = await fetch(`${getApiEndpoint("columns")}?${params}`);
      const data = await response.json();
    
      return {
        content: [{
          type: "text" as const,
          text: JSON.stringify(data, null, 2)
        }]
      };
    }
  • The tool metadata including title, description, and inputSchema with Zod validators for the parameters.
    {
      title: "Find Columns",
      description: "Find geological stratigraphic columns, rock layers, and geological history for any location worldwide. Use for geology, bedrock, formations, age dating, and stratigraphic analysis.",
      inputSchema: {
        lat: z.number().describe("A valid latitude in decimal degrees"),
        lng: z.number().describe("A valid longitude in decimal degrees"),
        adjacents: z.boolean().optional().describe("Include adjacent columns"),
        responseType: z.enum(["long", "short"]).default("long").describe("The length of response long or short"),
      }
    },
  • src/index.ts:914-944 (registration)
    The complete server.registerTool call that registers the 'find-columns' tool, including name, schema/metadata, and inline handler function.
    server.registerTool(
      "find-columns",
      {
        title: "Find Columns",
        description: "Find geological stratigraphic columns, rock layers, and geological history for any location worldwide. Use for geology, bedrock, formations, age dating, and stratigraphic analysis.",
        inputSchema: {
          lat: z.number().describe("A valid latitude in decimal degrees"),
          lng: z.number().describe("A valid longitude in decimal degrees"),
          adjacents: z.boolean().optional().describe("Include adjacent columns"),
          responseType: z.enum(["long", "short"]).default("long").describe("The length of response long or short"),
        }
      },
      async (request) => {
        const { lat, lng, adjacents, responseType } = request;
        const params = new URLSearchParams({
          lat: lat.toString(),
          lng: lng.toString(),
          adjacents: adjacents?.toString() ?? "false",
          response: responseType,
        });
        const response = await fetch(`${getApiEndpoint("columns")}?${params}`);
        const data = await response.json();
    
        return {
          content: [{
            type: "text" as const,
            text: JSON.stringify(data, null, 2)
          }]
        };
      }
    );
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. The description mentions what the tool does but lacks details on behavioral traits such as whether it's a read-only operation, potential rate limits, authentication needs, error handling, or what the output format looks like (e.g., structured data, text). For a tool with no annotations, this is a significant gap in transparency.

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, with two sentences that efficiently convey the purpose and usage. The first sentence states what the tool does, and the second provides usage context. There's no wasted text, but it could be slightly more structured by explicitly separating purpose from guidelines.

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 complexity (4 parameters, no output schema, no annotations), the description is moderately complete. It covers the purpose and general usage but lacks details on behavioral aspects and output. Without annotations or an output schema, the description should do more to compensate, such as hinting at return values or operational constraints, leaving some gaps 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?

The input schema has 100% description coverage, providing clear details for all parameters (lat, lng, adjacents, responseType). The description adds no specific parameter semantics beyond what's in the schema, such as explaining how 'adjacents' affects results or what 'long' vs 'short' response types entail. With high schema coverage, the baseline score is 3, as the schema handles the heavy lifting.

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: 'Find geological stratigraphic columns, rock layers, and geological history for any location worldwide.' It specifies the verb ('Find') and resource ('geological stratigraphic columns, rock layers, and geological history'), and mentions the scope ('any location worldwide'). However, it doesn't explicitly differentiate from sibling tools like 'find-units' or 'mineral-info', which might offer related geological data.

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

Usage Guidelines3/5

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

The description provides implied usage guidelines by stating 'Use for geology, bedrock, formations, age dating, and stratigraphic analysis.' This suggests contexts where the tool is applicable, but it doesn't explicitly state when to use this tool versus alternatives like 'find-units' or 'mineral-info', nor does it provide exclusions or prerequisites 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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