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mattjegan

eBird MCP Server

by mattjegan

get_nearby_hotspots

Find birding hotspots near specific coordinates using eBird data. Specify location, search radius, and recent activity to discover optimal birdwatching sites.

Instructions

Get birding hotspots near a location.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude
lngYesLongitude
backNoOnly hotspots visited in last N days
distNoSearch radius in kilometers
fmtNoResponse formatjson

Implementation Reference

  • The asynchronous handler function for the 'get_nearby_hotspots' tool. It constructs query parameters from the input arguments (lat, lng, dist, fmt, and optional back), makes an HTTP request to the '/ref/hotspot/geo' endpoint using the makeRequest helper, and returns the result as a JSON-formatted text content block.
    async (args) => {
      const params: Record<string, string | number | boolean> = {
        lat: args.lat,
        lng: args.lng,
        dist: args.dist,
        fmt: args.fmt,
      };
      if (args.back) params.back = args.back;
    
      const result = await makeRequest("/ref/hotspot/geo", params);
      return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }] };
    }
  • Zod input schema validating and describing the tool parameters: latitude, longitude, optional back days, distance radius (default 25km), and response format (json or csv, default json).
    {
      lat: z.number().min(-90).max(90).describe("Latitude"),
      lng: z.number().min(-180).max(180).describe("Longitude"),
      back: z.number().min(1).max(30).optional().describe("Only hotspots visited in last N days"),
      dist: z.number().min(0).max(500).default(25).describe("Search radius in kilometers"),
      fmt: z.enum(["json", "csv"]).default("json").describe("Response format"),
    },
  • src/index.ts:417-438 (registration)
    The server.tool() call that registers the 'get_nearby_hotspots' tool with its name, description, input schema, and handler function.
      "get_nearby_hotspots",
      "Get birding hotspots near a location.",
      {
        lat: z.number().min(-90).max(90).describe("Latitude"),
        lng: z.number().min(-180).max(180).describe("Longitude"),
        back: z.number().min(1).max(30).optional().describe("Only hotspots visited in last N days"),
        dist: z.number().min(0).max(500).default(25).describe("Search radius in kilometers"),
        fmt: z.enum(["json", "csv"]).default("json").describe("Response format"),
      },
      async (args) => {
        const params: Record<string, string | number | boolean> = {
          lat: args.lat,
          lng: args.lng,
          dist: args.dist,
          fmt: args.fmt,
        };
        if (args.back) params.back = args.back;
    
        const result = await makeRequest("/ref/hotspot/geo", params);
        return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }] };
      }
    );
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves data ('Get'), implying a read-only operation, but fails to describe critical behaviors like rate limits, authentication needs, pagination, or error handling. This leaves significant gaps in understanding how the tool behaves in practice.

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 front-loads the core purpose without unnecessary details. It wastes no words and is appropriately sized for a straightforward tool, earning a perfect score for conciseness and structure.

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 tool's moderate complexity (5 parameters, no output schema, no annotations), the description is incomplete. It lacks details on output format, error conditions, or behavioral constraints, which are essential for an agent to use the tool effectively. The high schema coverage helps, but the description does not compensate for other 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 description does not add any meaning beyond what the input schema provides, as it mentions no parameters. However, with 100% schema description coverage, the baseline score is 3, as the schema adequately documents all parameters (e.g., lat/lng for location, dist for radius, back for recency, fmt for format).

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 ('Get') and resource ('birding hotspots near a location'), making it immediately understandable. However, it does not explicitly differentiate from sibling tools like 'get_hotspots_in_region' or 'get_hotspot_info', which limits its score to 4 rather than 5.

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, such as 'get_hotspots_in_region' for regional searches or 'get_hotspot_info' for detailed hotspot data. It lacks explicit context, exclusions, or prerequisites, leaving usage decisions unclear.

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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