eia-energy-mcp-server

Lists child routes under a given path in the EIA dataset taxonomy. Start with no path to get the 14 top-level categories (electricity, petroleum, natural-gas, steo, aeo, ieo, seds, etc.), then drill into subcategories. Each result includes an isLeaf flag — leaf routes are queryable endpoints; non-leaf routes have children to browse. When isLeaf is true on the browsed path itself, switch to eia_describe_route.

Returns metadata for a leaf route: available facets with their valid values, data column names and units, frequency options, and date range. Call this before eia_query_route to discover valid facet IDs, facet values, column IDs, and frequency codes. Each facet returns a capped window of its values with value_count and values_truncated alongside; pass facet and values_offset to page through the rest of one facet. Facet values are fetched from separate EIA endpoints and merged — results are cached per-route for the process lifetime to minimize API calls.

Fuzzy text search across route names, descriptions, and category labels. Resolves natural-language queries like "electricity retail sales by state" or "natural gas imports" to matching route paths. Multi-term queries are also matched term by term, so combining a commodity, a metric, and a sector — "electricity price residential", "coal generation industrial sector" — reaches the route carrying that data even when no single entry reads like the whole phrase. STEO series names are indexed so queries like "ethanol net imports" or "crude oil production forecast" also resolve, and so are facet values, so a fuel type or sector term like "wind" or "anthracite coal" resolves to the route that exposes it, with filter_hint carrying the filter to pass on. Results include isLeaf so you know whether to browse further or query directly. Results with score > 0.72 are weak matches — try a more specific query or use eia_browse_routes to explore the taxonomy. The first call after server start waits 24-30s while the index warms, and at most 45s; every later call returns in milliseconds. Check indexComplete before reading anything into a short or empty result set.

Fetches data from a leaf route with optional facet filters, date range, frequency, and column selection. Use eia_describe_route first to discover valid facet IDs, facet values, column IDs, and frequency codes. Data values are strings in the response (EIA API returns all numeric values as strings, e.g. "9.13"); cast to DOUBLE in SQL when arithmetic is needed. Returns a preview inline; when canvas is enabled and more rows match than the preview holds, additional pages are fetched and the accumulated set is staged as a DataCanvas table — pass the returned dataset name to eia_dataframe_query for SQL. Every dataset a tenant stages lands in the same canvas, so tables from different routes cross-join by name with nothing to thread between calls.

List canvas dataframes (df_<id>) materialized by eia_query_route, with provenance, expiry, row count, and column schema. Drops entries for dataframes the canvas no longer holds before responding, so the list is always current. Pass a specific name to inspect one dataframe; omit to list all active dataframes for this tenant. A name that is not staged comes back as found=false alongside the handles that are, never as an empty list. Listing is not use: only an eia_dataframe_query statement naming a dataframe extends its expiry, so a dataframe polled with this tool and never queried still lapses on schedule.

Run a single-statement SELECT against canvas dataframes registered by eia_query_route. Standard DuckDB SQL — joins, aggregates, window functions, CTEs all supported. Reference dataframes by the df_<id> handles returned by eia_query_route or listed by eia_dataframe_describe. Read-only: writes, DDL, DROP, COPY, PRAGMA, ATTACH, and external-file table functions are rejected. System catalogs (information_schema, pg_catalog, sqlite_master, duckdb_*) are denied. EIA data values are VARCHAR — use CAST(col AS DOUBLE) for arithmetic and aggregation. Optional register_as chains results as a new dataframe with a fresh expiry. Every dataframe named in the statement has its expiry extended by the query.