INDIVIDUAL MCP TOOL

create_dataset

Create a new empty dataset on Autario.

autario.comnone authenticationAvailability not checked

Input schema

{}

Potential side effects detected · medium confidence · heuristic, not a guarantee.

CONNECT WITH APPROVAL

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.autario-com]
url = "https://autario.com/mcp"
enabled = true

Claude Code

.mcp.json

{
  "mcpServers": {
    "autario-com": {
      "type": "http",
      "url": "https://autario.com/mcp"
    }
  }
}

Claude Desktop

Settings → Connectors → Add custom connector

Name: autario-com
Remote MCP URL: https://autario.com/mcp

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "autario-com": {
      "url": "https://autario.com/mcp"
    }
  }
}

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

{
  "servers": {
    "autario-com": {
      "type": "http",
      "url": "https://autario.com/mcp"
    }
  }
}

Generic MCP

Client-specific MCP configuration

{
  "name": "autario-com",
  "transport": "streamable-http",
  "url": "https://autario.com/mcp"
}

MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

discover_by_topic — Discover the most relevant verified datasets for a given topic.
search_datasets — Search the Autario public data catalog.
get_dataset_info — Get full metadata for a specific dataset including title, description, publisher, category, keywords, row count, creation date, AND ontology fields (topic, subtopic, unit, frequency, entity_type, indicator_id, source_time_col, source_value_col, source_entity_col, data_granularity).
get_dataset_schema — Get the column names, data types, total row count, AND a machine-legible `datasheet` for a dataset.
query_dataset — Query data from a dataset with optional filtering, sorting, and field selection.
write_rows — Append rows of data to an existing dataset.
clear_rows — Delete all rows from a dataset while keeping the schema and columns intact.
delete_dataset — Permanently delete a dataset and all its data.