Skip to main content
Glama
Hug0x0

mcp-reunion

reunion_search_baby_names

Search first names given to babies in La Réunion since 2000 by prefix, year, and sex, sorted by count descending for naming trend and demographic analysis.

Instructions

Search first names given to babies born in La Réunion (department 974) by year, since 2000. Each row gives: usual first name (uppercase), year of birth, department, sex code, and number of children given that name that year. Sorted by count descending. Source: INSEE Fichier des prénoms via data.regionreunion.com. Useful for naming trend analysis, demographic studies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoFirst name prefix match (case-insensitive — auto-uppercased). Example: "marie" matches "MARIE", "MARIE-CLAIRE", "MARIETTE"
yearNoBirth year filter (4 digits, 2000-present), e.g. 2020
sexNoSex code: "1" for boys, "2" for girls
limitNoMax rows to return (1-500, default 100)

Implementation Reference

  • Registration of the 'reunion_search_baby_names' tool via server.tool() — also includes the schema and handler inline.
    server.tool(
      'reunion_search_baby_names',
      'Search first names given to babies born in La Réunion (department 974) by year, since 2000. Each row gives: usual first name (uppercase), year of birth, department, sex code, and number of children given that name that year. Sorted by count descending. Source: INSEE Fichier des prénoms via data.regionreunion.com. Useful for naming trend analysis, demographic studies.',
      {
        name: z.string().optional().describe('First name prefix match (case-insensitive — auto-uppercased). Example: "marie" matches "MARIE", "MARIE-CLAIRE", "MARIETTE"'),
        year: z.number().int().optional().describe('Birth year filter (4 digits, 2000-present), e.g. 2020'),
        sex: z.enum(['1', '2']).optional().describe('Sex code: "1" for boys, "2" for girls'),
        limit: z.number().int().min(1).max(500).default(100).describe('Max rows to return (1-500, default 100)'),
      },
      async ({ name, year, sex, limit }) => {
        try {
          const data = await client.getRecords<RecordObject>(DATASET_NAMES, {
            where: buildWhere([
              name ? `preusuel LIKE ${quote(`${name.toUpperCase()}%`)}` : undefined,
              year !== undefined ? `annais = ${quote(String(year))}` : undefined,
              sex ? `sexe = ${quote(sex)}` : undefined,
            ]),
            order_by: 'nombre DESC',
            limit,
          });
          return jsonResult({
            total_rows: data.total_count,
            names: data.results.map((row) => ({
              sex: pickString(row, ['sexe']),
              first_name: pickString(row, ['preusuel']),
              year: pickString(row, ['annais']),
              department: pickString(row, ['dpt']),
              count: pickNumber(row, ['nombre']),
            })),
          });
        } catch (error) {
          return errorResult(error instanceof Error ? error.message : 'Failed to search baby names');
        }
      }
    );
  • Zod schema defining input parameters: optional name (prefix string), year (int), sex (enum '1'/'2'), and limit (int 1-500, default 100).
    {
      name: z.string().optional().describe('First name prefix match (case-insensitive — auto-uppercased). Example: "marie" matches "MARIE", "MARIE-CLAIRE", "MARIETTE"'),
      year: z.number().int().optional().describe('Birth year filter (4 digits, 2000-present), e.g. 2020'),
      sex: z.enum(['1', '2']).optional().describe('Sex code: "1" for boys, "2" for girls'),
      limit: z.number().int().min(1).max(500).default(100).describe('Max rows to return (1-500, default 100)'),
    },
  • Handler function that queries the 'prenomsdpt974depuis2000' dataset on data.regionreunion.com, filters by name prefix, year, sex, sorts by count descending, and returns mapped results with sex, first_name, year, department, and count.
      async ({ name, year, sex, limit }) => {
        try {
          const data = await client.getRecords<RecordObject>(DATASET_NAMES, {
            where: buildWhere([
              name ? `preusuel LIKE ${quote(`${name.toUpperCase()}%`)}` : undefined,
              year !== undefined ? `annais = ${quote(String(year))}` : undefined,
              sex ? `sexe = ${quote(sex)}` : undefined,
            ]),
            order_by: 'nombre DESC',
            limit,
          });
          return jsonResult({
            total_rows: data.total_count,
            names: data.results.map((row) => ({
              sex: pickString(row, ['sexe']),
              first_name: pickString(row, ['preusuel']),
              year: pickString(row, ['annais']),
              department: pickString(row, ['dpt']),
              count: pickNumber(row, ['nombre']),
            })),
          });
        } catch (error) {
          return errorResult(error instanceof Error ? error.message : 'Failed to search baby names');
        }
      }
    );
  • Dataset ID constant 'prenomsdpt974depuis2000' used by the tool to query the OpenDataSoft API.
    const DATASET_NAMES = 'prenomsdpt974depuis2000';
  • registerAdministrationTools is called from registerAllTools to wire up all administration tools including reunion_search_baby_names.
        voters: pickNumber(row, ['votants']),
        blank: pickNumber(row, ['blancs']),
        null_votes: pickNumber(row, ['nuls']),
        expressed: pickNumber(row, ['exprimes']),
        panel_num: pickNumber(row, ['ndegpanneau']),
        candidate_last_name: pickString(row, ['nom']),
        candidate_first_name: pickString(row, ['prenom']),
        candidate_sex: pickString(row, ['sexe']),
        political_label: pickString(row, ['nuance']),
        votes: pickNumber(row, ['voix']),
        votes_pct_expressed: pickNumber(row, ['voix_exp']),
      };
    }
    
    export function registerAdministrationTools(server: McpServer): void {
Behavior4/5

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

With no annotations provided, the description carries full burden. It explains the output format (columns, sorting, source) and notes case-insensitivity for the name parameter. While it doesn't cover all edge cases (e.g., default behavior with no parameters), it provides key behavioral details beyond the schema.

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 compact four-sentence paragraph. It front-loads the purpose, then efficiently describes output, sorting, and source. No redundant or wasted language.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, the description covers the tool's purpose, scope, output structure, sorting, and data source. For a tool with 4 parameters and no output schema, this is sufficiently complete for correct 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?

Schema description coverage is 100%, so baseline is 3. The description does not add significant new meaning to parameters beyond what the schema already provides (e.g., prefix match, year range, sex enum). It describes the output but not parameter details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches first names given to babies born in La Réunion by year since 2000, with a specific geographic and temporal scope. It distinguishes itself from sibling tools (e.g., reunion_search_schools) by focusing on baby names, making its purpose unambiguous.

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 mentions usefulness for naming trend analysis and demographic studies, implying appropriate contexts. However, it does not explicitly state when not to use the tool or provide alternatives, leaving the guidance implied rather than explicit.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Hug0x0/mcp-reunion'

If you have feedback or need assistance with the MCP directory API, please join our Discord server