Tools
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_agencies
Entry point for discovery — enumerate OECD's statistical departments before searching.
- Returns agency IDs (e.g.
OECD.SDD.NAD,OECD.ELS,OECD.EDU) and dataflow counts - Useful for scoping
oecd_search_datasetsby department (national accounts, labour, education, etc.)
oecd_search_datasets
Search the full catalog of 1,500+ OECD dataflows by keyword or department.
- Token-matching across dataflow names — finds GDP, PISA, trade, inflation, and other datasets by description
- Optional
agency_idfilter scopes results to a specific statistical department - Returns
flow_refvalues (e.g.OECD.SDD.NAD,DSD_NAAG@DF_NAAG_I) — pass directly tooecd_get_dataset_infooroecd_query_dataset - Fetches and filters in-memory; the full catalog is ~800 KB and bounded (OECD adds datasets weekly, not continuously)
oecd_get_dataset_info
Inspect a dataflow's structure before querying.
- Returns all dimensions in key order (position 1, 2, 3 …) — dimension order is required to construct the dot-delimited key for
oecd_query_dataset - Shows codelist references for each dimension — pass to
oecd_get_dimension_valuesto resolve human-readable names to SDMX codes - Surfaces
NonProductionDataflowflag — marks experimental or deprecated dataflows - Required before calling
oecd_query_dataseton an unfamiliar dataflow
oecd_get_dimension_values
Resolve human-readable names (countries, measures) to SDMX codes.
- Returns all valid code + label pairs for a single dimension (e.g.
REF_AREA→USA/United States,DEU/Germany) - The
REF_AREAcodelist has 570+ entries and is returned in full - Use substring matching on the returned list to find the right code before building a key
oecd_query_dataset
Fetch observations from an OECD dataflow filtered by dimension key and time range.
- Accepts a dot-delimited key (e.g.
A.USA+DEU.B1GQ_R.PC.) where empty segments are wildcards and+separates multiple values - Optional
start_period/end_periodbound the time range (ISO format:2010,2010-Q1) - Decodes SDMX-JSON index notation (
0:0:2:3:0) into human-readable row objects with dimension labels - Every response row includes
source: "OECD"per OECD terms of use - Small results (few countries, narrow time range): all observations returned inline
- Large results (multi-country, multi-year time-series): returns a
canvas_id+truncated: true— useoecd_dataframe_describeto list tables, thenoecd_dataframe_queryfor SQL analytics
oecd_dataframe_describe / oecd_dataframe_query
SQL 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")
Resources
| 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.
Features
Built on @cyanheads/mcp-ts-core:
- Declarative tool, resource, and prompt definitions — single file per primitive, framework handles registration and validation
- Unified error handling — handlers throw, framework catches, classifies, and formats
- Pluggable auth:
none,jwt,oauth - Swappable storage backends:
in-memory,filesystem,Supabase,Cloudflare KV/R2/D1 - Structured logging with optional OpenTelemetry tracing
- STDIO and Streamable HTTP transports
OECD-specific:
- Keyless access — no API key required; OECD SDMX 2.1 REST API is fully public
- Covers 1,500+ dataflows across 20+ OECD statistical departments (national accounts, employment, inflation, trade, education, health, environment, taxation, inequality)
AllDimensionsobservation mode — one-pass SDMX-JSON decoding into flat row objects; no nested series key reconstructionoecd_query_datasetmaterializes large observation sets (multi-country time-series) on a DuckDB DataCanvas for in-conversation SQL analytics- OECD source attribution (
source: "OECD") on every observation row per OECD terms of use
Agent-friendly output:
- Workflow-aware tool surface —
flow_reffrom search flows directly into info, values, and query tools without reconstruction - Spill signaling —
truncated: true+canvas_idtells the agent to switch to SQL instead of parsing a truncated inline list - Full SDMX decoding server-side — agents see
{ ref_area: "United States", measure: "Gross domestic product", obs_value: 26054 }, not raw index arrays
Getting started
Add 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
Prerequisites
- Bun v1.3.11 or higher (or Node.js v24+).
- No API key required — OECD SDMX is a free, public API.
Installation
- Clone the repository:
git clone https://github.com/cyanheads/oecd-mcp-server.git
- Navigate into the directory:
cd oecd-mcp-server
- Install dependencies:
bun install
- Configure environment:
cp .env.example .env
# edit .env — most vars are optional; no API key required
Configuration
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.
Running the server
Local development
-
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
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.
Project structure
| 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/. |
Development guide
See CLAUDE.md for development guidelines and architectural rules. The short version:
- Handlers throw, framework catches — no
try/catchin tool logic - Use
ctx.logfor request-scoped logging,ctx.statefor tenant-scoped storage - Register new tools and resources via the barrels in
src/mcp-server/*/index.ts - Wrap external API calls: validate raw SDMX-JSON → normalize to domain type → return output schema; never fabricate missing fields
Contributing
Issues and pull requests are welcome. Run checks and tests before submitting:
bun run devcheck
bun run test
License
Apache-2.0 — see LICENSE for details.