eBird MCP Server

get_top_100

Retrieve the top 100 bird observation contributors for a specific date and region, ranking by species or checklist counts using eBird data.

Instructions

Get the top 100 contributors on a given date.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "region_code": "<region_code>",
      "year": "<year>",
      "month": "<month>",
      "day": "<day>"
    },
    "name": "get_top_100"
  }
}

Input Schema

Name	Required	Description	Default
`region_code`	Yes	Country or subnational1 code
`year`	Yes	Year
`month`	Yes	Month
`day`	Yes	Day of month
`ranked_by`	No	'spp' for species count, 'cl' for checklist count	spp
`max_results`	No	Limit results

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jan 4, 2026

TDQS

C2.9/5.0

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 mentions retrieving data ('Get'), implying a read-only operation, but fails to specify critical traits like rate limits, authentication needs, pagination, or the format of returned results (e.g., list of contributors with details). This leaves significant gaps in understanding how the tool behaves beyond basic input-output.

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 words. It directly states what the tool does, making it easy to parse quickly, and every part of the sentence contributes essential information, earning its place.

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 complexity (6 parameters, no annotations, no output schema), the description is insufficiently complete. It doesn't explain the return format (e.g., what data 'contributors' includes), behavioral constraints, or how it integrates with sibling tools. For a data retrieval tool with multiple inputs and no structured output, more context is needed to ensure proper agent usage.

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 adds minimal semantic context beyond the input schema, which has 100% coverage with detailed parameter descriptions. It implies date-based filtering via 'on a given date,' but the schema already covers 'year,' 'month,' and 'day' parameters explicitly. No additional syntax or usage nuances are provided, so the baseline score of 3 is appropriate as the schema does most of the work.

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 target resource ('top 100 contributors'), and specifies the context ('on a given date'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_regional_statistics' or 'get_recent_observations' that might also involve contributor data, leaving some ambiguity about uniqueness.

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 which sibling tools might overlap in functionality (e.g., 'get_regional_statistics' for broader data or 'get_recent_observations' for time-based queries). It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage from parameters alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.