Eia Energy MCP Server
未申請Browse and query the U.S. Energy Information Administration API v2 — electricity, petroleum, natural gas, coal, forecasts, and more via MCP. STDIO or Streamable HTTP.
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eia_browse_routes
Lists child routes under a given path in the EIA dataset taxonomy. Start at root to see top-level categories, then drill into subcategories and leaf routes.
eia_dataframe_describe
Lists active DataCanvas dataframes created by prior eiaqueryroute calls that passed stage: true. Only exposed when a canvas is configured. Shows table name, column names and types, row count, expiry, and the query that produced it. A handle that is not staged comes back as a miss alongside the handl
eia_dataframe_drop
Drops a DataCanvas dataframe, freeing its memory. Only exposed when a canvas is configured and EIADATAFRAMEDROPENABLED=true.
eia_dataframe_query
Runs a read-only SQL SELECT across DataCanvas dataframes, referenced by their df<id> table names. Only exposed when a canvas is configured.
eia_describe_route
Returns metadata for a leaf route: available facets with valid values, data column names, frequency options, units, and date range. Call before eiaqueryroute to understand filter options. Facet values come back capped, with facet and valuesoffset to page one facet.
eia_query_route
Fetches data from a leaf route with optional facet filters, date range, frequency, and column selection. Returns a preview; pass stage: true to also page past it and stage the matching rows as a DataCanvas table for SQL analysis.
eia_search_routes
Fuzzy text search across route names, descriptions, category labels, STEO series names, and facet values. Resolves natural-language queries like "electricity retail sales by state" or a fuel type like "wind" to matching route paths.
indexComplete
reports whether the answer was ranked against the whole corpus; when it is false, indexGaps names the routes and index passes that are missing, so a short result set is never mistaken for a settled one
score
runs 0 (exact) to 1 (no match), lower is better; above 0.72 the match is unreliable and the query is worth narrowing. bun run eval:search scores a labelled query battery against a live corpus, which is where that number comes from
values_offset
applies to every facet in the response. One past a facet's last value empties that facet's window and returns a notice naming the facet and its valuecount, so an overshoot never reads like a fully enumerated facet