Israel Statistics MCP

Exposes Israeli Central Bureau of Statistics price indices through the Model Context Protocol (MCP), enabling LLM agents and applications to query economic indicators like CPI, housing costs, and commodity prices via standardized MCP tool calls. The server implements MCP resource and tool endpoints that translate natural language queries into CBS API requests, parse structured statistical responses, and return formatted data to the calling client.

Automatically generates MCP-compliant tool schemas that map CBS API parameters (index type, date range, category filters) into callable functions with proper type validation, descriptions, and required/optional field declarations. The server introspects available CBS indices and constructs tool definitions that LLM clients can invoke, handling parameter marshaling and response formatting transparently.

Transforms raw CBS API responses (typically XML or JSON with Hebrew field names and nested structures) into normalized MCP-compatible JSON with English field names, flattened hierarchies, and consistent timestamp/numeric formatting. The parser handles CBS-specific quirks like multiple index versions, seasonal adjustments, and metadata fields, presenting a clean interface to MCP clients.

Implements MCP resource endpoints that expose a catalog of available CBS price indices, their descriptions, supported date ranges, and category hierarchies. Clients can query this metadata layer to discover what data is available before making specific statistical queries, enabling agents to dynamically construct appropriate requests based on available resources.

Enables querying CBS price indices across specified date ranges, returning time-series data with values for each reporting period (typically monthly). The capability handles date range validation, period alignment (e.g., converting arbitrary date ranges to CBS reporting periods), and returns structured arrays of timestamp-value pairs suitable for trend analysis and comparison.

Supports querying multiple CBS indices simultaneously and returning comparative results, enabling analysis of relationships between different economic indicators (e.g., CPI vs housing costs vs food prices). The capability handles index-to-index alignment (ensuring comparable time periods), normalization for different scales, and structured output suitable for correlation or trend comparison.

Enables filtering CBS price indices by category (e.g., food, housing, energy, transportation) and navigating hierarchical category structures to identify relevant indices. The capability exposes category taxonomies and supports queries like 'all food-related price indices' or 'housing subcategories', allowing agents to dynamically construct category-specific queries.

Tracks and reports metadata about CBS data freshness, including publication dates, revision status, and update frequency for each index. The capability enables clients to assess data recency and confidence, informing LLM reasoning about whether data is current enough for decision-making. Includes detection of revised or preliminary data flags.