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kshayk

AviBase MCP Server

by kshayk

get_birds_by_region

Find bird species by geographic region using the AviBase dataset. Enter a region name to retrieve birds found in that area.

Instructions

Find birds by geographic region or range (e.g., Madagascar, Australia, Africa, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
regionYesGeographic region to search for in bird ranges
limitNoMaximum number of results to return (default: 50)

Implementation Reference

  • The handler function that executes the tool logic: destructures region and limit args, calls the /range API endpoint, and returns a formatted text response with bird data.
      async handleGetBirdsByRegion(args) {
        const { region, limit = 50 } = args;
        const endpoint = `/range?region=${encodeURIComponent(region)}&limit=${limit}`;
        const response = await this.makeAPIRequest(endpoint);
    
        return {
          content: [
            {
              type: 'text',
              text: `# Birds of ${region}
    
    🌍 **${response.pagination.totalItems}** bird records found in ${region}
    
    **Regional species:**
    ${response.data.slice(0, 15).map((bird, i) => `${i + 1}. **${bird.Scientific_name}**
       - Common name: ${bird.English_name_AviList || 'No common name'}
       - Family: ${bird.Family}
       - Conservation: ${bird.IUCN_Red_List_Category || 'Not assessed'}`).join('\n\n')}
    
    ${response.pagination.hasNext ? `\n*Note: Showing first ${response.data.length} of ${response.pagination.totalItems} total records for this region.*` : ''}`,
            },
          ],
        };
      }
  • The input schema and metadata for the get_birds_by_region tool, registered in the ListTools response.
    {
      name: 'get_birds_by_region',
      description: 'Find birds by geographic region or range (e.g., Madagascar, Australia, Africa, etc.).',
      inputSchema: {
        type: 'object',
        properties: {
          region: {
            type: 'string',
            description: 'Geographic region to search for in bird ranges',
          },
          limit: {
            type: 'number',
            description: 'Maximum number of results to return (default: 50)',
            default: 50,
          },
        },
        required: ['region'],
      },
    },
  • mcp-server.js:300-301 (registration)
    The switch case registration that dispatches tool calls to the handleGetBirdsByRegion handler.
    case 'get_birds_by_region':
      return await this.handleGetBirdsByRegion(args);
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe how it behaves: no information about return format (e.g., list of birds with what fields?), pagination (implied by 'limit' parameter but not explained), error handling, or performance characteristics. The description is functional but lacks operational context needed for an agent to use it effectively.

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 extremely concise—a single sentence with helpful examples in parentheses. Every word earns its place: 'Find birds by geographic region or range' establishes the core function, and '(e.g., Madagascar, Australia, Africa, etc.)' provides concrete guidance without verbosity. It's front-loaded with the essential information.

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 no annotations and no output schema, the description is incomplete for a tool with two parameters and multiple siblings. It doesn't explain what the tool returns (bird objects? names only?), how results are structured, or how it differs from similar tools like 'search_birds'. For a query tool in a rich sibling environment, more contextual information would help an agent use it correctly.

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?

Schema description coverage is 100%, so the schema already fully documents both parameters ('region' and 'limit'). The description adds no additional parameter semantics beyond what's in the schema—it doesn't clarify region format (e.g., are continent names like 'Africa' valid?), search behavior (exact match vs. substring), or result ordering. 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 tool's purpose: 'Find birds by geographic region or range' with specific examples. It uses a clear verb ('Find') and resource ('birds') with a specific scope ('by geographic region or range'). However, it doesn't explicitly differentiate from sibling tools like 'search_birds' or 'get_birds_by_taxonomy', 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'search_birds' (which might allow more flexible queries) or 'get_birds_by_taxonomy' (which filters by classification). There's no context about prerequisites, exclusions, or comparative advantages.

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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