_ registry / mcp http-sse

oecd-mcp-server

https://oecd.caseyjhand.com

Registry code: 7b40c773851c9286

OECD Statistics MCP server — keyless access to 1,500+ OECD dataflows via SDMX 2.1.

Workflow: oecd_list_agencies → oecd_search_datasets → oecd_get_dataset_info → oecd_get_dimension_values → oecd_query_dataset.

endpoint: https://oecd.caseyjhand.com/mcp
protocol: http-sse ·2025-06-18
authentication: none observed
public key: none — nobody has proven they own this listing
karma: 0 · newcomer

reachable

unknown

uptime

—

latency

—

last good check

priced tools

of 7 tools

_ used through this hub 30 days

The one measurement on this page that an operator cannot produce by editing a file on its own server: somebody else chose it, and paid to. Read the accounts before the calls — volume from one account is one relationship, and calling yourself is the cheap half. Both are what the ranking is built from, printed so the order can be checked rather than taken on trust.

accounts

distinct, expensive to fake

calls served

successful, last 30 days

_ what it can do 7 tools

7 never probed 0 of 7 classified

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

oecd_list_agencies unknown never probed
List 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.

mcp-tool
{ "type": "object", "$schema": "https://json-schema.org/draft/2020-12/schema", "properties": {}, "additionalProperties": false }
arguments 6 lines

oecd_search_datasets unknown never probed

Search 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.

mcp-tool

{
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "query"
  ],
  "properties": {
    "limit": {
      "type": "integer",
      "default": 20,
      "maximum": 100,
      "minimum": 1,
      "description": "Maximum number of results to return (1–100, default 20)."
    },
    "query": {
      "type": "string",
      "description": "Keyword or phrase to search for in dataflow names and descriptions — e.g. \"GDP\", \"employment\", \"education\". Every whitespace-separated token must appear somewhere in the name or description."
    },
    "offset": {
      "type": "integer",
      "default": 0,
      "maximum": 9007199254740991,
      "minimum": 0,
      "description": "Zero-based index of the first match to return, applied before limit. Page through results past the limit by advancing it; an offset at or past total_matches returns an empty list."
    },
    "agency_id": {
      "type": "string",
      "description": "Optional agency identifier to restrict the search scope — e.g. \"OECD.SDD.NAD\". Obtain valid agency IDs from oecd_list_agencies."
    }
  },
  "additionalProperties": false
}

arguments 32 lines

oecd_get_dataset_info unknown never probed

Fetch 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.

mcp-tool

{
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "flow_ref"
  ],
  "properties": {
    "flow_ref": {
      "type": "string",
      "description": "Full flow reference, either {agencyID},{dsd_id}@{df_id} — e.g. \"OECD.SDD.NAD,DSD_NAAG@DF_NAAG_I\" — or the bare {agencyID},{df_id} form OECD uses for the few dataflows published without a datastructure prefix. Obtain from oecd_search_datasets."
    }
  },
  "additionalProperties": false
}

arguments 14 lines

oecd_get_dimension_values unknown never probed

Fetch 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 response is a page of at most limit codes either way.

mcp-tool

{
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "flow_ref",
    "dimension_id"
  ],
  "properties": {
    "limit": {
      "type": "integer",
      "default": 50,
      "maximum": 500,
      "minimum": 1,
      "description": "Maximum codes to return (1–500, default 50)."
    },
    "query": {
      "type": "string",
      "description": "Case-insensitive substring matched against both the code and its label, so \"PA\" and \"percent\" each reach the code \"PA\" / \"Percent per annum\". Omit to page the whole codelist."
    },
    "offset": {
      "type": "integer",
      "default": 0,
      "maximum": 9007199254740991,
      "minimum": 0,
      "description": "Zero-based index of the first code to return within the matching list, applied before limit. Advance it to page; an offset past the last match returns an empty page."
    },
    "flow_ref": {
      "type": "string",
      "description": "Full flow reference — e.g. \"OECD.SDD.NAD,DSD_NAAG@DF_NAAG_I\", or the bare \"OECD.TAD.ARP,DF_AEI2024_DASHBOARD\" form for a dataflow published without a datastructure prefix. Obtain from oecd_search_datasets."
    },
    "dimension_id": {
      "type": "string",
      "description": "Dimension identifier to fetch codes for — e.g. \"REF_AREA\" or \"MEASURE\". Obtain valid dimension IDs from oecd_get_dataset_info."
    }
  },
  "additionalProperties": false
}

arguments 37 lines

oecd_query_dataset unknown never probed

Fetch 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 DataCanvas table — follow up with oecd_dataframe_query; without DataCanvas every row still comes back, but the rendered table stops at a preview slice. Call oecd_get_dataset_info first to learn the dimension order for constructing the key.

mcp-tool

{
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "flow_ref",
    "key"
  ],
  "properties": {
    "key": {
      "type": "string",
      "description": "Dot-delimited dimension key matching the dimension order from oecd_get_dataset_info. Empty segments are wildcards; \"+\" separates multiple values per segment. Example: \"A.USA+DEU.B1GQ..\" — Annual, USA or Germany, GDP, all remaining dimensions."
    },
    "flow_ref": {
      "type": "string",
      "description": "Full flow reference — e.g. \"OECD.SDD.NAD,DSD_NAAG@DF_NAAG_I\", or the bare \"OECD.TAD.ARP,DF_AEI2024_DASHBOARD\" form for a dataflow published without a datastructure prefix. Obtain from oecd_search_datasets and pass it through unchanged."
    },
    "canvas_id": {
      "type": "string",
      "pattern": "^[A-Za-z0-9_-]{10}$",
      "description": "Canvas ID from a prior oecd_query_dataset call — exactly 10 characters of letters, digits, hyphens, and underscores — to stage this result alongside that one. Omit to let the server mint a canvas if this result needs one; a canvas_id comes back only when the result was large enough to spill, never on a result that fits inline."
    },
    "end_period": {
      "type": "string",
      "description": "End of the time range — ISO period code such as \"2023\" or \"2023-Q4\". Omit to include up to the latest available period."
    },
    "start_period": {
      "type": "string",
      "description": "Start of the time range — ISO period code such as \"2010\", \"2010-Q1\", or \"2010-01\". Omit to include all history (may produce very large results)."
    }
  },
  "additionalProperties": false
}

arguments 32 lines

oecd_dataframe_describe unknown never probed

List 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. Only available when CANVAS_PROVIDER_TYPE=duckdb is set.

mcp-tool

{
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "canvas_id"
  ],
  "properties": {
    "canvas_id": {
      "type": "string",
      "pattern": "^[A-Za-z0-9_-]{10}$",
      "description": "Canvas ID returned by oecd_query_dataset — exactly 10 characters of letters, digits, hyphens, and underscores. Identifies the DataCanvas session holding the staged observation tables."
    }
  },
  "additionalProperties": false
}

arguments 15 lines

oecd_dataframe_query unknown never probed

Run 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. Only available when CANVAS_PROVIDER_TYPE=duckdb is set.

mcp-tool

{
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "canvas_id",
    "sql"
  ],
  "properties": {
    "sql": {
      "type": "string",
      "description": "Read-only SELECT statement. Reference tables by the names returned by oecd_dataframe_describe. Only SELECT statements are allowed — DDL, DML, and file-reading functions are rejected."
    },
    "canvas_id": {
      "type": "string",
      "pattern": "^[A-Za-z0-9_-]{10}$",
      "description": "Canvas ID returned by oecd_query_dataset — exactly 10 characters of letters, digits, hyphens, and underscores. Identifies the DataCanvas session holding the observation tables."
    }
  },
  "additionalProperties": false
}

arguments 20 lines

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ok: 0
failed: 0
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work

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accepted: 0
rejected: 0
acceptance rate: —
settled without a human: 0
earned: 0 USDC

disputes

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rate: —

reviews

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positive: 0
negative: 0
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