Gives Claude direct access to 1,500+ OECD statistical datasets through their SDMX API without requiring any API key. You get seven tools: search the full catalog by keyword or agency, inspect dataflow schemas and dimension codelists, then query observations with dimension filters and time ranges. Large result sets automatically spill to a DuckDB canvas where you can run SQL aggregations and analytics. The server decodes SDMX-JSON into flat rows and handles datasets across national accounts, employment, trade, PISA education scores, health metrics, and more. Useful when you need authoritative cross-country economic data for research, analysis, or visualization without leaving the LLM conversation or managing API credentials.
MCP_LOG_LEVELdefault: infoSets the minimum log level for output (e.g., 'debug', 'info', 'warn').
MCP_HTTP_HOSTdefault: 127.0.0.1The hostname for the HTTP server.
MCP_HTTP_PORTdefault: 3010The port to run the HTTP server on.
MCP_HTTP_ENDPOINT_PATHdefault: /mcpThe endpoint path for the MCP server.
MCP_AUTH_MODEdefault: noneAuthentication mode to use: 'none', 'jwt', or 'oauth'.
Search, explore, and query 1,500+ OECD statistical datasets (national accounts, employment, trade, PISA, health) via SDMX via MCP. STDIO or Streamable HTTP.
Five discovery and data tools plus two SQL analytics tools for large query results:
| Tool | Description |
|---|---|
oecd_list_agencies | List OECD SDMX agencies and the number of dataflows each publishes |
oecd_search_datasets | Search 1,500+ OECD dataflows by keyword or theme |
oecd_get_dataset_info | Fetch a dataflow's dimensions, key order, and codelist references |
oecd_get_dimension_values | Fetch valid codes and labels for one dimension (countries, measures, frequencies) |
oecd_query_dataset | Fetch observations filtered by dimension key and time range; spills large results to DataCanvas |
oecd_dataframe_describe | List DataCanvas tables and columns staged by a prior oecd_query_dataset spill |
oecd_dataframe_query | Run a read-only SQL SELECT against DataCanvas tables |
oecd_list_agenciesEntry point for discovery — enumerate OECD's statistical departments before searching.
OECD.SDD.NAD, OECD.ELS, OECD.EDU) and dataflow countsoecd_search_datasets by department (national accounts, labour, education, etc.)oecd_search_datasetsSearch the full catalog of 1,500+ OECD dataflows by keyword or department.
agency_id filter scopes results to a specific statistical departmentflow_ref values (e.g. OECD.SDD.NAD,DSD_NAAG@DF_NAAG_I) — pass directly to oecd_get_dataset_info or oecd_query_datasetoecd_get_dataset_infoInspect a dataflow's structure before querying.
oecd_query_datasetoecd_get_dimension_values to resolve human-readable names to SDMX codesNonProductionDataflow flag — marks experimental or deprecated dataflowsoecd_query_dataset on an unfamiliar dataflowoecd_get_dimension_valuesResolve human-readable names (countries, measures) to SDMX codes.
REF_AREA → USA/United States, DEU/Germany)REF_AREA codelist has 570+ entries and is returned in fulloecd_query_datasetFetch observations from an OECD dataflow filtered by dimension key and time range.
A.USA+DEU.B1GQ_R.PC.) where empty segments are wildcards and + separates multiple valuesstart_period / end_period bound the time range (ISO format: 2010, 2010-Q1)0:0:2:3:0) into human-readable row objects with dimension labelssource: "OECD" per OECD terms of usecanvas_id + truncated: true — use oecd_dataframe_describe to list tables, then oecd_dataframe_query for SQL analyticsoecd_dataframe_describe / oecd_dataframe_querySQL analytics over observation data staged by oecd_query_dataset.
When oecd_query_dataset returns truncated: true, the full result is staged on a DuckDB-backed DataCanvas. Pass the canvas_id to:
oecd_dataframe_describe — list staged table names and their columns. Run this first to discover the schema before writing SQL.oecd_dataframe_query — run a single-statement SQL SELECT. Supports aggregates, window functions, GROUP BY, ORDER BY, and standard DuckDB SQL.Requires CANVAS_PROVIDER_TYPE=duckdb. Read-only: writes, DDL, and system catalog access are rejected.
Typical workflow for a large query:
oecd_query_dataset → { canvas_id, truncated: true, rows: [preview...] }
→ oecd_dataframe_describe(canvas_id) → table/column names
→ oecd_dataframe_query(canvas_id, "SELECT ref_area, AVG(obs_value) FROM df_... GROUP BY ref_area")
| Type | Name | Description |
|---|---|---|
| Resource | oecd://dataflow/{agency_id}/{flow_id} | Dimension metadata for a single OECD dataflow — same content as oecd_get_dataset_info |
{flow_id} is the combined {dsd_id}@{df_id} string with @ percent-encoded as %40. Example: oecd://dataflow/OECD.SDD.NAD/DSD_NAAG%40DF_NAAG_I.
All resource data is also reachable via tools. Use oecd_get_dataset_info for the same content.
Built on @cyanheads/mcp-ts-core:
none, jwt, oauthin-memory, filesystem, Supabase, Cloudflare KV/R2/D1OECD-specific:
AllDimensions observation mode — one-pass SDMX-JSON decoding into flat row objects; no nested series key reconstructionoecd_query_dataset materializes large observation sets (multi-country time-series) on a DuckDB DataCanvas for in-conversation SQL analyticssource: "OECD") on every observation row per OECD terms of useAgent-friendly output:
flow_ref from search flows directly into info, values, and query tools without reconstructiontruncated: true + canvas_id tells the agent to switch to SQL instead of parsing a truncated inline list{ ref_area: "United States", measure: "Gross domestic product", obs_value: 26054 }, not raw index arraysAdd the following to your MCP client configuration file.
{
"mcpServers": {
"oecd-mcp-server": {
"type": "stdio",
"command": "bunx",
"args": ["@cyanheads/oecd-mcp-server@latest"],
"env": {
"MCP_TRANSPORT_TYPE": "stdio",
"MCP_LOG_LEVEL": "info"
}
}
}
}
Or with npx (no Bun required):
{
"mcpServers": {
"oecd-mcp-server": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@cyanheads/oecd-mcp-server@latest"],
"env": {
"MCP_TRANSPORT_TYPE": "stdio",
"MCP_LOG_LEVEL": "info"
}
}
}
}
Or with Docker:
{
"mcpServers": {
"oecd-mcp-server": {
"type": "stdio",
"command": "docker",
"args": [
"run", "-i", "--rm",
"-e", "MCP_TRANSPORT_TYPE=stdio",
"ghcr.io/cyanheads/oecd-mcp-server:latest"
]
}
}
}
To enable DataCanvas SQL analytics for large query results, add CANVAS_PROVIDER_TYPE=duckdb:
{
"mcpServers": {
"oecd-mcp-server": {
"type": "stdio",
"command": "bunx",
"args": ["@cyanheads/oecd-mcp-server@latest"],
"env": {
"MCP_TRANSPORT_TYPE": "stdio",
"CANVAS_PROVIDER_TYPE": "duckdb"
}
}
}
}
For Streamable HTTP, set the transport and start the server:
MCP_TRANSPORT_TYPE=http MCP_HTTP_PORT=3010 bun run start:http
# Server listens at http://localhost:3010/mcp
git clone https://github.com/cyanheads/oecd-mcp-server.git
cd oecd-mcp-server
bun install
cp .env.example .env
# edit .env — most vars are optional; no API key required
All configuration is validated at startup via Zod schemas in src/config/server-config.ts. Key environment variables:
| Variable | Description | Default |
|---|---|---|
OECD_BASE_URL | OECD SDMX REST API base URL. | https://sdmx.oecd.org/public/rest |
OECD_TIMEOUT_MS | Per-request timeout in milliseconds. | 30000 |
CANVAS_PROVIDER_TYPE | Canvas engine. Set to duckdb to enable DataCanvas for large oecd_query_dataset results. | none |
MCP_TRANSPORT_TYPE | Transport: stdio or http. | stdio |
MCP_HTTP_PORT | Port for HTTP server. | 3010 |
MCP_AUTH_MODE | Auth mode: none, jwt, or oauth. | none |
MCP_LOG_LEVEL | Log level (RFC 5424). | info |
LOGS_DIR | Directory for log files (Node.js only). | <project-root>/logs |
OTEL_ENABLED | Enable OpenTelemetry instrumentation. | false |
See .env.example for the full list of optional overrides.
Build and run:
# One-time build
bun run rebuild
# Run the built server
bun run start:stdio
# or
bun run start:http
Run checks and tests:
bun run devcheck # Lint, format, typecheck, security
bun run test # Vitest test suite
bun run lint:mcp # Validate MCP definitions against spec
docker build -t oecd-mcp-server .
docker run --rm -p 3010:3010 oecd-mcp-server
The Dockerfile defaults to HTTP transport, stateless session mode, and logs to /var/log/oecd-mcp-server. OpenTelemetry peer dependencies are installed by default — build with --build-arg OTEL_ENABLED=false to omit them.
| Directory | Purpose |
|---|---|
src/index.ts | createApp() entry point — registers tools/resources and initializes services. |
src/config/ | Server-specific environment variable parsing and validation with Zod. |
src/mcp-server/tools/definitions/ | Tool definitions (*.tool.ts) — seven tools for OECD data discovery and retrieval. |
src/mcp-server/resources/definitions/ | Resource definitions (*.resource.ts) — the oecd://dataflow resource. |
src/services/oecd-structure/ | OECD SDMX structure service — dataflows, data structures, codelists. |
src/services/oecd-data/ | OECD SDMX data service — observations, SDMX-JSON decoding, DataCanvas spillover. |
src/services/canvas-accessor/ | DataCanvas accessor — registers and exposes the framework canvas instance to tools. |
tests/ | Unit and integration tests mirroring src/. |
See CLAUDE.md for development guidelines and architectural rules. The short version:
try/catch in tool logicctx.log for request-scoped logging, ctx.state for tenant-scoped storagesrc/mcp-server/*/index.tsIssues and pull requests are welcome. Run checks and tests before submitting:
bun run devcheck
bun run test
Apache-2.0 — see LICENSE for details.
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