# datarails-finance-os-mcp

Source: https://glimind.com/server/pypi%2Fdatarails-finance-os-mcp
Registry id: `pypi/datarails-finance-os-mcp`
Status: unknown

## Install

```json
{
  "mcpServers": {
    "datarails-finance-os-mcp": {
      "command": "uvx",
      "args": [
        "datarails-finance-os-mcp"
      ]
    }
  }
}
```

Claude Code:

```sh
claude mcp add datarails-finance-os-mcp -- uvx datarails-finance-os-mcp
```

## Tools (17)

- `aggregate_table_data`: Grouped aggregations with no row limit
- `auth_status`: Check current authentication status
- `authenticate`: Connect to Datarails via OAuth (opens browser)
- `detect_anomalies`: Auto-detect data quality issues
- `disable`: Disconnect — revoke tokens and clear credentials
- `execute_query`: Custom SQL-like queries (max 1000 rows)
- `extract_financials`: Extract validated financial data to Excel
- `generate_intelligence_workbook`: FP&A intelligence workbook (Excel)
- `get_field_distinct_values`: Unique values for a field
- `get_records_by_filter`: Fetch filtered records (max 500 rows)
- `get_sample_records`: Random sample for quick inspection
- `get_table_schema`: Get column names, types, relationships
- `get_workflow_guide`: Guided workflows for common analysis tasks
- `list_finance_tables`: Discover available tables
- `profile_categorical_fields`: Cardinality, frequencies for categorical fields
- `profile_numeric_fields`: Min/max/avg/outliers for numeric fields
- `profile_table_summary`: Row counts, data quality score

Measured by Glimind (https://glimind.com): MCP handshake + tool list only, no tool is ever called. CC BY 4.0.