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mcp-reunion

reunion_get_consumer_price_index

Retrieve monthly consumer price index data for La Réunion. Filter by period, COICOP category, and population to track inflation, deflate nominal values, or compare price trends.

Instructions

INSEE monthly Indice des Prix à la Consommation (IPC, consumer price index) for La Réunion. Time series broken down by COICOP category (Classification of Individual Consumption by Purpose) and population (whole population vs urban households). Use it to track inflation, deflate nominal values to real, or compare price evolution across categories (food, energy, housing, transport, etc.). Returns period, COICOP code/label, base year, population, zone, IDBANK identifier, index value. Sorted most recent first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNoPeriod prefix match in YYYY-MM format. Examples: "2023" (whole year), "2023-12" (specific month)
coicop_codeNoCOICOP category code prefix. Examples: "01" food and beverages, "02" alcohol/tobacco, "04" housing/water/energy, "07" transport, "11" restaurants/hotels, "00" general index
typeNoType label prefix match (e.g. "Indice général", "Indice mensuel")
limitNoMax rows to return (1-500, default 100)

Implementation Reference

  • The handler function for 'reunion_get_consumer_price_index' tool. It queries the INSEE CPI dataset (insee-indices-des-prix-a-la-consommation-a-la-reunion-valeurs-mensuelles) via the OpenDataSoft client, filtering by period, COICOP code, and type. Returns monthly consumer price index data for La Réunion sorted most recent first.
    server.tool(
      'reunion_get_consumer_price_index',
      'INSEE monthly Indice des Prix à la Consommation (IPC, consumer price index) for La Réunion. Time series broken down by COICOP category (Classification of Individual Consumption by Purpose) and population (whole population vs urban households). Use it to track inflation, deflate nominal values to real, or compare price evolution across categories (food, energy, housing, transport, etc.). Returns period, COICOP code/label, base year, population, zone, IDBANK identifier, index value. Sorted most recent first.',
      {
        period: z.string().optional().describe('Period prefix match in YYYY-MM format. Examples: "2023" (whole year), "2023-12" (specific month)'),
        coicop_code: z.string().optional().describe('COICOP category code prefix. Examples: "01" food and beverages, "02" alcohol/tobacco, "04" housing/water/energy, "07" transport, "11" restaurants/hotels, "00" general index'),
        type: z.string().optional().describe('Type label prefix match (e.g. "Indice général", "Indice mensuel")'),
        limit: z.number().int().min(1).max(500).default(100).describe('Max rows to return (1-500, default 100)'),
      },
      async ({ period, coicop_code, type, limit }) => {
        try {
          const data = await client.getRecords<RecordObject>(DATASET_CPI, {
            where: buildWhere([
              period ? `periode LIKE ${quote(`${period}%`)}` : undefined,
              coicop_code ? `coicop_code LIKE ${quote(`${coicop_code}%`)}` : undefined,
              type ? `type LIKE ${quote(`${type}%`)}` : undefined,
            ]),
            order_by: 'periode DESC',
            limit,
          });
          return jsonResult({
            total_rows: data.total_count,
            series: data.results.map((row) => ({
              period: pickString(row, ['periode']),
              code: pickString(row, ['code']),
              type: pickString(row, ['type']),
              sub_type: pickString(row, ['sous_type']),
              coicop_code: pickString(row, ['coicop_code']),
              coicop_label: pickString(row, ['coicop_texte']),
              base: pickString(row, ['base']),
              population: pickString(row, ['population']),
              zone: pickString(row, ['zone']),
              index_name: pickString(row, ['indice']),
              value: pickNumber(row, ['valeur']),
              idbank: pickString(row, ['insee_idbank']),
            })),
          });
        } catch (error) {
          return errorResult(error instanceof Error ? error.message : 'Failed to fetch CPI');
        }
      }
    );
  • Input schema for the tool defining parameters: period (YYYY-MM prefix), coicop_code (category code prefix), type (label prefix), and limit (max rows, 1-500, default 100).
    {
      period: z.string().optional().describe('Period prefix match in YYYY-MM format. Examples: "2023" (whole year), "2023-12" (specific month)'),
      coicop_code: z.string().optional().describe('COICOP category code prefix. Examples: "01" food and beverages, "02" alcohol/tobacco, "04" housing/water/energy, "07" transport, "11" restaurants/hotels, "00" general index'),
      type: z.string().optional().describe('Type label prefix match (e.g. "Indice général", "Indice mensuel")'),
      limit: z.number().int().min(1).max(500).default(100).describe('Max rows to return (1-500, default 100)'),
    },
  • Tool registration via server.tool() call in registerEconomyTools(), binding the name 'reunion_get_consumer_price_index' to its schema and handler.
    server.tool(
      'reunion_get_consumer_price_index',
      'INSEE monthly Indice des Prix à la Consommation (IPC, consumer price index) for La Réunion. Time series broken down by COICOP category (Classification of Individual Consumption by Purpose) and population (whole population vs urban households). Use it to track inflation, deflate nominal values to real, or compare price evolution across categories (food, energy, housing, transport, etc.). Returns period, COICOP code/label, base year, population, zone, IDBANK identifier, index value. Sorted most recent first.',
      {
        period: z.string().optional().describe('Period prefix match in YYYY-MM format. Examples: "2023" (whole year), "2023-12" (specific month)'),
        coicop_code: z.string().optional().describe('COICOP category code prefix. Examples: "01" food and beverages, "02" alcohol/tobacco, "04" housing/water/energy, "07" transport, "11" restaurants/hotels, "00" general index'),
        type: z.string().optional().describe('Type label prefix match (e.g. "Indice général", "Indice mensuel")'),
        limit: z.number().int().min(1).max(500).default(100).describe('Max rows to return (1-500, default 100)'),
      },
      async ({ period, coicop_code, type, limit }) => {
        try {
          const data = await client.getRecords<RecordObject>(DATASET_CPI, {
            where: buildWhere([
              period ? `periode LIKE ${quote(`${period}%`)}` : undefined,
              coicop_code ? `coicop_code LIKE ${quote(`${coicop_code}%`)}` : undefined,
              type ? `type LIKE ${quote(`${type}%`)}` : undefined,
            ]),
            order_by: 'periode DESC',
            limit,
          });
          return jsonResult({
            total_rows: data.total_count,
            series: data.results.map((row) => ({
              period: pickString(row, ['periode']),
              code: pickString(row, ['code']),
              type: pickString(row, ['type']),
              sub_type: pickString(row, ['sous_type']),
              coicop_code: pickString(row, ['coicop_code']),
              coicop_label: pickString(row, ['coicop_texte']),
              base: pickString(row, ['base']),
              population: pickString(row, ['population']),
              zone: pickString(row, ['zone']),
              index_name: pickString(row, ['indice']),
              value: pickNumber(row, ['valeur']),
              idbank: pickString(row, ['insee_idbank']),
            })),
          });
        } catch (error) {
          return errorResult(error instanceof Error ? error.message : 'Failed to fetch CPI');
        }
      }
    );
  • buildWhere helper used to construct the ODSQL WHERE clause from optional filter conditions.
    export function buildWhere(
      conditions: Array<string | undefined | null | false>
    ): string | undefined {
      const valid = conditions.filter((condition): condition is string => Boolean(condition));
      return valid.length > 0 ? valid.join(' AND ') : undefined;
    }
  • ReunionClient.getRecords method used to fetch records from the CPI dataset on data.regionreunion.com.
      async getRecords<T extends RecordObject = RecordObject>(
        datasetId: string,
        params: ODSQueryParams = {}
      ): Promise<ODSResponse<T>> {
        const url = this.buildUrl(`/catalog/datasets/${datasetId}/records`, params);
    
        if (REFERENTIAL_DATASETS.has(datasetId)) {
          const now = Date.now();
          const cached = this.recordsCache.get(url);
          if (cached && cached.expiresAt > now) {
            return cached.value as ODSResponse<T>;
          }
          const value = await this.fetchJson<ODSResponse<T>>(url);
          this.recordsCache.set(url, { value, expiresAt: now + REFERENTIAL_TTL_MS });
          return value;
        }
    
        return this.fetchJson<ODSResponse<T>>(url);
      }
    
      /**
       * Clear the in-memory caches. Intended for tests.
       */
      clearCaches(): void {
        this.metadataCache.clear();
        this.recordsCache.clear();
      }
    
      /**
       * Fetch aggregated data from a dataset
       */
      async getAggregates<T extends RecordObject = RecordObject>(
        datasetId: string,
        select: string,
        options: {
          where?: string;
          groupBy?: string;
          orderBy?: string;
          limit?: number;
        } = {}
      ): Promise<ODSResponse<T>> {
        const params: Record<string, string | number | undefined> = { select };
        if (options.where) params.where = options.where;
        if (options.groupBy) params.group_by = options.groupBy;
        if (options.orderBy) params.order_by = options.orderBy;
        if (options.limit !== undefined) params.limit = options.limit;
    
        const url = this.buildUrl(`/catalog/datasets/${datasetId}/aggregates`, params);
        return this.fetchJson<ODSResponse<T>>(url);
      }
    
      /**
       * Search across all datasets
       */
      async searchDatasets(query: string): Promise<CatalogResponse> {
        const url = this.buildUrl('/catalog/datasets', {
          where: `search(${quote(query)})`,
          limit: 20,
        });
        return this.fetchJson<CatalogResponse>(url);
      }
    
      /**
       * List datasets with an optional raw ODSQL where clause.
       */
      async listDatasets(
        options: { where?: string; limit?: number; offset?: number } = {}
      ): Promise<CatalogResponse> {
        const url = this.buildUrl('/catalog/datasets', {
          where: options.where,
          limit: options.limit ?? 20,
          offset: options.offset,
        });
        return this.fetchJson<CatalogResponse>(url);
      }
    
      /**
       * Fetch dataset metadata from the catalog
       */
      async getDatasetMetadata(datasetId: string): Promise<DatasetMetadata | undefined> {
        if (!this.metadataCache.has(datasetId)) {
          const promise = this.fetchJson<CatalogResponse>(
            this.buildUrl('/catalog/datasets', {
              where: `dataset_id = ${quote(datasetId)}`,
              limit: 1,
            })
          ).then((data) => data.results[0]);
    
          this.metadataCache.set(datasetId, promise);
        }
    
        return this.metadataCache.get(datasetId);
      }
    
      /**
       * Check whether a dataset currently exists in the public catalog
       */
      async datasetExists(datasetId: string): Promise<boolean> {
        return Boolean(await this.getDatasetMetadata(datasetId));
      }
    
      /**
       * Resolve the first matching field name for a dataset
       */
      async resolveField(
        datasetId: string,
        candidates: string[]
      ): Promise<string | undefined> {
        const metadata = await this.getDatasetMetadata(datasetId);
        const fields = metadata?.fields ?? [];
    
        if (fields.length === 0) {
          return candidates[0];
        }
    
        const byNormalizedName = new Map(
          fields.map((field) => [normalizeText(field.name), field.name] as const)
        );
    
        for (const candidate of candidates) {
          const direct = byNormalizedName.get(normalizeText(candidate));
          if (direct) {
            return direct;
          }
        }
    
        const fieldNames = fields.map((field) => field.name);
        for (const candidate of candidates) {
          const normalizedCandidate = normalizeText(candidate);
          const partial = fieldNames.find((fieldName) =>
            normalizeText(fieldName).includes(normalizedCandidate)
          );
          if (partial) {
            return partial;
          }
        }
    
        return candidates[0];
      }
    
      /**
       * Build URL with query parameters
       */
      private buildUrl(
        path: string,
        params: Record<string, string | number | undefined>
      ): string {
        const normalizedPath = path.startsWith('/') ? path.slice(1) : path;
        const url = new URL(normalizedPath, this.baseUrl);
    
        for (const [key, value] of Object.entries(params)) {
          if (value !== undefined && value !== null && value !== '') {
            url.searchParams.set(key, String(value));
          }
        }
    
        return url.toString();
      }
    
      /**
       * Execute HTTP request with retries and timeout handling
       */
      private async fetchJson<T>(url: string, remainingRetries = this.maxRetries): Promise<T> {
        const controller = new AbortController();
        const timeoutId = setTimeout(() => controller.abort(), this.timeout);
    
        try {
          const response = await fetch(url, {
            method: 'GET',
            headers: {
              Accept: 'application/json',
              'User-Agent': 'mcp-reunion/1.0',
            },
            signal: controller.signal,
          });
    
          if (!response.ok) {
            const errorText = await response.text();
            if (response.status >= 500 && remainingRetries > 0) {
              await this.delay(250);
              return this.fetchJson<T>(url, remainingRetries - 1);
            }
            throw new Error(
              `API error ${response.status}: ${response.statusText}. ${errorText}`
            );
          }
    
          return (await response.json()) as T;
        } catch (error) {
          if (error instanceof Error) {
            if (error.name === 'AbortError') {
              throw new Error(`Request timeout after ${this.timeout}ms`);
            }
    
            if (remainingRetries > 0 && this.isRetryableError(error)) {
              await this.delay(250);
              return this.fetchJson<T>(url, remainingRetries - 1);
            }
    
            throw error;
          }
          throw new Error('Unknown error occurred');
        } finally {
          clearTimeout(timeoutId);
        }
      }
    
      private isRetryableError(error: Error): boolean {
        return /fetch failed|ECONNRESET|ETIMEDOUT|ENOTFOUND|EAI_AGAIN/i.test(error.message);
      }
    
      private async delay(ms: number): Promise<void> {
        await new Promise((resolve) => setTimeout(resolve, ms));
      }
    }
    
    // Singleton instance
    export const client = new ReunionClient();
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses the return fields (period, COICOP code/label, etc.) and sorting order ('sorted most recent first'). It implies read-only behavior and no destructive side effects. While it doesn't mention authentication or rate limits, the description is transparent about the data and behavior.

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 four sentences, each serving a distinct purpose: source identification, breakdown and use cases, return fields, and sorting order. It is front-loaded with the most critical information and contains no redundant or vague statements.

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

Completeness4/5

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

Given the complexity (4 optional parameters, no output schema, no annotations), the description covers the main aspects: data source, breakdown, use cases, return fields, and sorting. It lacks details on pagination beyond the limit parameter, but the limit parameter is explained in the schema. The description is sufficiently complete for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with parameter descriptions. The description adds value by providing example values for coicop_code ('01', '02', '00') and explaining the prefix match behavior. This supplements the schema, which only gives generic descriptions.

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 retrieves the INSEE monthly consumer price index for La Réunion, broken down by COICOP category and population. It specifies the verb ('get'), the resource ('consumer price index'), and the scope ('for La Réunion'). This differentiates it from all sibling tools, which cover other topics.

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

Usage Guidelines4/5

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

The description explicitly states use cases: 'track inflation, deflate nominal values to real, or compare price evolution across categories.' It indirectly indicates when to use it (any CPI-related task). However, it does not mention when not to use it or alternative tools, but given no sibling does CPI, this is adequate.

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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