Context7
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Descripción del creador (original en inglés)
Search and query 1,500+ OECD statistical datasets via SDMX. Keyless.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
MCP_LOG_LEVEL, OECD_DATAFRAME_DROP_ENABLEDNecesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Funciona en Claude para web, escritorio y móvil:
https://oecd.caseyjhand.com/mcpAbre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"oecd": {
"command": "npx",
"args": [
"-y",
"@cyanheads/oecd-mcp-server"
],
"env": {
"MCP_LOG_LEVEL": "your-value",
"OECD_DATAFRAME_DROP_ENABLED": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add --transport http oecd https://oecd.caseyjhand.com/mcpclaude mcp add oecd --env MCP_LOG_LEVEL=your-value --env OECD_DATAFRAME_DROP_ENABLED=your-value -- npx -y @cyanheads/oecd-mcp-serverCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"oecd": {
"url": "https://oecd.caseyjhand.com/mcp"
}
}
}Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"oecd": {
"command": "npx",
"args": [
"-y",
"@cyanheads/oecd-mcp-server"
],
"env": {
"MCP_LOG_LEVEL": "your-value",
"OECD_DATAFRAME_DROP_ENABLED": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"oecd": {
"type": "http",
"url": "https://oecd.caseyjhand.com/mcp"
}
}
}Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"oecd": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@cyanheads/oecd-mcp-server"
],
"env": {
"MCP_LOG_LEVEL": "your-value",
"OECD_DATAFRAME_DROP_ENABLED": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
ChatGPT solo se conecta a servidores en internet:
https://oecd.caseyjhand.com/mcpLos nombres de los menús pueden variar un poco según el plan y con el tiempo.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
MCP_LOG_LEVEL envOECD_DATAFRAME_DROP_ENABLED envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Nombres y descripciones de las herramientas tal como los informó el servidor el 6 nov 2026. Los escribió el creador, no nosotros; los mostramos como texto sin formato.
oecd_list_agenciesList OECD SDMX agencies, the directorate each belongs to, and the number of dataflows each publishes. Use to discover agency IDs before filtering oecd_search_datasets by department.
oecd_search_datasetsSearch OECD dataflows by keyword or theme, matching against dataflow names and descriptions. Returns flow_ref identifiers, names, and agency IDs for use with oecd_get_dataset_info.
oecd_get_dataset_infoFetch a dataflow's dimensions, their order, and how to construct a query key. Returns per-dimension names, codelist references, and position in the dot-delimited key. Required before calling oecd_query_dataset to understand key structure.
oecd_get_dimension_valuesFetch the valid codes and labels for one dimension of a dataflow. Use to resolve human-readable names (countries, measures) to SDMX codes before querying with oecd_query_dataset. Pass query to match a code or label by substring — codelists run to a thousand-plus entries, and the
oecd_query_datasetFetch observations from an OECD dataflow filtered by a dimension key and optional time range. Returns decoded rows (one per observation) with dimension and attribute labels, and values already scaled by the observation unit multiplier. Large multi-country time-series spill to a D
oecd_dataframe_describeList tables and columns staged on a DataCanvas by a prior oecd_query_dataset spill. Call this before oecd_dataframe_query to discover exact table and column names for SQL. Unavailable when the server runs with DataCanvas disabled.
oecd_dataframe_queryRun a read-only SQL SELECT against OECD observation tables staged on a DataCanvas by oecd_query_dataset. Call oecd_dataframe_describe first to discover exact table and column names, then use this tool for aggregation, filtering, GROUP BY, JOIN, and window functions. Returns up to
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub cyanheads, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Respondió en 547 ms (HTTP 200)
No hace falta iniciar sesión
Leímos 7 descripciones de herramientas y no encontramos instrucciones ocultas para la IA
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 3 de 3 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Funciona de las dos formas: instálalo en tu computadora o conéctate a la versión en la nube.
El repo de GitHub cambió por última vez –, y la última versión (0.6.1) llegó al registro hace 4 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. Se conecta por URL, así que también funcionan las apps que aceptan servidores MCP remotos, como ChatGPT en modo desarrollador.
En la misma categoría: Context7, Codebase Memory, Exa
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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@cyanheads/oecd-mcp-server Search, explore, and query 1,500+ OECD statistical datasets (national accounts, employment, trade, education, health) from the OECD SDMX API via MCP. STDIO or Streamable HTTP. 8 Tools • 1 Resource • 1 Skill
Public Hosted Server: https://oecd.caseyjhand.com/mcp
OECD statistics across 1,500+ datasets on national accounts, employment, trade, education, and health. Search datasets, inspect their dimensions, query observations, and run SQL over large multi-country time series. No API key required.
Five discovery and data tools plus three DataCanvas tools for large query results:
| Tool | Description |
|---|---|
oecd_list_agencies | List OECD SDMX agencies with their directorate 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_dataframe_drop | Drop a staged DataCanvas table or view once the analysis is done — opt-in via OECD_DATAFRAME_DROP_ENABLED=true |
| Resource | Description |
|---|---|
oecd://dataflow/{agency_id}/{flow_id} | Dimension metadata for a single OECD dataflow — same content as oecd_get_dataset_info |
All resource data is also reachable via tools. Use oecd_get_dataset_info for the same content.
| Skill | Description |
|---|---|
oecd-guide | Building SDMX keys, confirming which series a dataflow carries, and reading results without mixing breakdowns, units, or country aggregates. Served over MCP at skill://oecd-guide/SKILL.md |
oecd_list_agencies toolOECD.SDD.NAD) with its directorate name and dataflow count, sorted by countESTAT, IAEG-SDGs) carry no directorateoecd_search_datasets toolquery token-matched across dataflow names and descriptions; optional agency_id scope; limit (1–100) and offset paging with total_matchesflow_ref — the identifier every other tool takes — and matched_in (name, description, or both)oecd_get_dataset_info toolflow_ref; returns every dimension in key order with its concept name and codelist reference, plus a key_example for oecd_query_datasetinvalid_flow_ref for a string that is not a flow reference and dataflow_not_found for one OECD does not publishoecd_get_dimension_values toolflow_ref and dimension_id; optional query substring-matches both code and labellimit (1–500, default 50) and offset page the matches, with the full match count when more remainoecd_query_dataset toolflow_ref plus a dot-delimited key (+ for multiple values, empty segments as wildcards) and optional start_period / end_periodvalue is pre-multiplied by value_scaletruncated: true, canvas_id, and table_name; without a canvas every row stays in structuredContent and only the rendered table is capped (content_table_capped)notice naming the canvas and table: inspect columns with oecd_dataframe_describe, then use oecd_dataframe_query for SQL over the full result. Fitting results allocate no new canvas; an explicit canvas_id is checked before the download, so a stale one fails as canvas_not_found without spending an OECD request.oecd_dataframe_describe toolcanvas_id oecd_query_dataset returned; lists each staged table and view with its row count and column names and typesoecd_dataframe_query toolcanvas_id plus one read-only SQL SELECT; writes, DDL, and system-catalog access are rejectedlimit (default 100) returns up to 1,000 rows per call, within 1 MiB of row data; a limit from 1,001 to 10,000 is served at 1,000 with a noticetruncated: true marks a result with more rows than it returned, and its notice names how to reach the rest; row_count counts the rows returnedquery_timeoutoecd_dataframe_drop toolcanvas_id plus a table_name as oecd_dataframe_describe lists it; returns the dropped object's kind and the remaining_tablesOECD_DATAFRAME_DROP_ENABLED=trueoecd://dataflow/{agency_id}/{flow_id} resourceoecd_get_dataset_info, as application/json{flow_id} is {dsd_id}@{df_id} with @ encoded as %40 (e.g. oecd://dataflow/OECD.SDD.NAD/DSD_NAAG%40DF_NAAG_I), or the bare {df_id}Built on @cyanheads/mcp-ts-core: stdio and Streamable HTTP transports, pluggable auth (none / jwt / oauth), swappable storage (in-memory, filesystem, Supabase, Cloudflare KV/R2/D1), structured logging with optional OpenTelemetry tracing.
OECD-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 analytics; the oecd_dataframe_* tools work on it; DataCanvas is on by default and CANVAS_PROVIDER_TYPE=none disables itAgent-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", UNIT_MULT: "Billions", value: 26054614000000, value_scale: 1000000000 }, not raw index arraysConnect to the hosted instance, no install:
claude mcp add --transport http oecd-mcp-server https://oecd.caseyjhand.com/mcp
Or run it locally:
claude mcp add oecd-mcp-server -- npx -y @cyanheads/oecd-mcp-server
For other clients, add this to the MCP config file:
{
"mcpServers": { "oecd-mcp-server": { "command": "npx", "args": ["-y", "@cyanheads/oecd-mcp-server"] } } }
No API key is needed — OECD SDMX is a free, public API. DataCanvas SQL analytics over large query results is on by default; set CANVAS_PROVIDER_TYPE=none to get capped inline previews instead. For Docker or a source build, see Running the server.
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. Must be an https origin that answers directly — no redirect is followed, so a plaintext http:// origin fails instead of being upgraded to https. | https://sdmx.oecd.org/public/rest |
OECD_TIMEOUT_MS | Per-request timeout in milliseconds. | 30000 |
CANVAS_PROVIDER_TYPE | Canvas engine. With duckdb, a large oecd_query_dataset result spills to a queryable table instead of just capping the rendered preview; with none, every row still comes back in structuredContent and only the rendered table is capped. | duckdb |
OECD_DATAFRAME_DROP_ENABLED | Set to true to register oecd_dataframe_drop. Off, the tool is listed as disabled and clients cannot call it. | false |
MCP_TRANSPORT_TYPE | Transport: stdio or http. | stdio |
MCP_HTTP_PORT | Port for HTTP server. | 3010 |
MCP_SESSION_MODE | HTTP session posture: stateful, stateless, or auto. The server declares stateless in source — it keeps no per-session state, and a DataCanvas handle is keyed by canvas_id — so set this only to override that. | stateless |
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). | /logs |
LOG_TOOL_FAILURE_PAYLOADS | Log each failed tool call's arguments and result, redacted by key name and capped at LOG_TOOL_FAILURE_PAYLOAD_MAX_BYTES (default 16384). A secret inside a free-form value is not redacted. | false |
OTEL_ENABLED | Enable OpenTelemetry instrumentation. | false |
See .env.example for the full list of optional
Solo se muestra el principio; lee el resto en el repo