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mcp server

imf-mcp-server

Query IMF SDMX 3.0 macroeconomic dataflows — WEO, BOP, CPI, exchange rates, 190 countries.

Description as published by the maintainer. Source

  • version 0.2.6
  • active

active — Most recent push to the repository was 2026-08-06.

What this server can do

5 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.

imf_dataframe_describe(canvas_id)
List DataCanvas tables and columns staged by a prior imf_query_dataset call. Returns each table's name, row count, and column schema (name + DuckDB type). Required before imf_dataframe_query to discover the table and column names for SQL. Required: canvas_id.
imf_dataframe_query(sql, canvas_id)
Run a read-only SQL SELECT against a DataCanvas table staged by imf_query_dataset. Supports multi-country comparisons, time-series aggregation, and cross-indicator joins. Requires imf_dataframe_describe first to discover table and column names. One SELECT statement per call; a leading WITH … SELECT (CTE) is accepted. DML and DDL are rejected. Required: canvas_id, sql.
imf_get_database(version, agency_id, dataflow_id, codelist_filter)
Fetch a dataflow's dimension list with a codelist preview for each dimension. Resolves human-readable terms to SDMX codes (e.g. "United States" → USA, "real GDP growth" → NGDP_RPCH). Required before imf_query_dataset — SDMX keys are opaque without codelist lookups. Each codelist is capped at the first 50 entries by default; set codelist_filter to return every entry matching a substring, or read the imf://database/{dataflow_id} resource for complete codelists. Country codes are ISO 3-letter (USA, GBR, DEU), not ISO 2-letter (US, GB, DE). The key_format field shows the exact dimension order required by imf_query_dataset. Note: codelists enumerate the code universe, not actual coverage — valid codes can still return no_data if the combination has no series in this dataflow. Required: dataflow_id.
imf_list_databases(limit, filter, offset, include_vintages)
List IMF SDMX dataflows available on the portal. Entry point for every query: imf_get_database and imf_query_dataset both require a dataflow id obtained here. Vintage (historical snapshot) dataflows such as WEO_2025_OCT_VINTAGE are excluded by default; set include_vintages=true to include them. Results are paged — 50 per call by default, adjustable with limit and offset — and total_count reports how many dataflows matched. Descriptions are shortened here; imf_get_database returns the full text for a single dataflow.
imf_query_dataset(key, version, agency_id, canvas_id, end_period, dataflow_id, start_period)
Query an IMF SDMX dataflow by dimension key over a time range. Returns observations with time_period, value, and status, plus the unit, scale, and decimals of each series — a key resolving to several series carries one entry per series in series_metadata, since unit and scale differ between them. Requires imf_get_database first to obtain the correct key_format and valid dimension codes. Country codes are ISO 3-letter (USA, GBR, DEU — not US, GB, DE). Key format: dot-separated codes in DSD keyPosition order (e.g. USA.NGDP_RPCH.A for WEO). Every position must carry a code: use + to combine codes (e.g. USA+GBR.NGDP_RPCH.A) and * to match every code at a position (e.g. *.NGDP_RPCH.A for all countries). Codelists from imf_get_database enumerate the code universe, not actual coverage — valid codes can still return no_data if the combination has no series. start_period and end_period must be valid period strings (YYYY, YYYY-SN, YYYY-QN, YYYY-MM, or YYYY-MM-DD) with start_period no later than end_period; malformed or reversed ranges are rejected. A bound covers the whole period it names, so end_period 2023 includes 2023-M12 and 2023-Q4. Large analytical result sets (multi-country, long time range) spill to DataCanvas; imf_dataframe_query provides SQL analysis of spilled results. Required: dataflow_id, key.

Last successful function declaration observed on . Source: https://imf.caseyjhand.com/mcp. We list what the server declared; we do not call any of these functions.

Endpoint status observed on . Source: https://imf.caseyjhand.com/mcp.

Signals

These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.

Signal Value What it measures Window Observed Source
GitHub stars 1 Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. cumulative, all time GitHub
Last commit 2026-08-06 Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. point in time GitHub
Open issues 4 Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. as of fetch GitHub
Latest published version 0.2.6 Latest version string the maintainer published to the registry. as of fetch Model Context Protocol
Registry record last updated 2026-08-06 When the registry record was last updated by its maintainer. point in time Model Context Protocol
License Apache-2.0 Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. as of fetch GitHub
First listed in the MCP Registry 2026-08-06 Date this server was first published to the official MCP Registry. Not a usage or quality measure. point in time Model Context Protocol
repository status active The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. as of fetch GitHub
mcp tools declared 5 tools Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. as of probe imf.caseyjhand.com
mcp endpoint status ok The server listed 5 functions when asked. as of probe imf.caseyjhand.com

Where to get it

Related, by what their authors tagged them

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These share tags the maintainers applied themselves, such as cyanheads, economics, sdmx, statistics. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.

This is not a recommendation and not a test result. It is a map of what the authors said their work is about.

Also from cyanheads

How the author describes it

Topics the maintainer set on GitHub: ai-agents, ai-tools, cyanheads, economics, imf, mcp, mcp-server, model-context-protocol, sdmx, statistics, typescript.

This record as data

Every field on this page, with its source and observation date, is in the catalog JSON. Fetch the whole kind at once instead of parsing this HTML.

GET /api/v1/entries/mcp_server.json

Sources

  1. cyanheads/imf-mcp-server on GitHub — GitHub, observed , trust tier 3.
  2. Tools declared by the MCP server at https://imf.caseyjhand.com/mcp — imf.caseyjhand.com, observed , trust tier 4.
  3. Official MCP Registry — Model Context Protocol, observed , trust tier 1.