/explore-tables

Explore Your Data

Discover what tables and data are available in your Datarails Finance OS account.

Step 1: Verify Connection

Start by calling list_finance_tables to verify the connection is active.

If the tool call fails: The Datarails connector isn't connected. Tell the user to click the "+" button next to the prompt, select Connectors, find Datarails, and click Connect. Then STOP.

Step 2: List All Tables

Use: mcp__datarails-finance-os__list_finance_tables

Step 3: Present Available Data

Create a friendly overview:

Your Datarails Data

I found [X] tables in your account:

Financial Data

Table	Records	Description
[Table Name] (ID: XXXX)	~[count]	[inferred purpose]

KPI/Metrics Data

Table	Records	Description
[Table Name] (ID: XXXX)	~[count]	[inferred purpose]

Other Tables

Table	Records	Description
[Table Name] (ID: XXXX)	~[count]	[inferred purpose]

Want to explore a specific table? Just ask:

• "Show me the columns in [table name]"
• "What kind of data is in [table name]?"
• "Show me a sample from [table name]"

Step 4: Explore Specific Table (on request)

When user asks about a specific table:

Get Schema

Use: mcp__datarails-finance-os__get_table_schema
Parameters:
  table_id: <requested_table_id>

Get Sample Data

Use: mcp__datarails-finance-os__get_sample_records
Parameters:
  table_id: <requested_table_id>
  n: 10

Present Table Details

Table: [Table Name]

Columns Available

Column	Type	Description
[Column 1]	[type]	[inferred meaning]
[Column 2]	[type]	[inferred meaning]
...	...	...

Sample Data

Here's what the data looks like:

[Show 3-5 sample records in a readable format]

Quick Stats

• Total records: ~[count]
• Date range: [if date field exists]
• Key categories: [if categorical fields exist]

What would you like to do with this data?

• Analyze it (expenses, revenue, etc.)
• Check data quality
• Compare to budget

Inferring Table Purpose

Help users understand their tables based on column names:

Likely Financial/P&L Table if contains:

• Amount, Value, Sum columns
• Account hierarchy (L1, L2, L3)
• Scenario (Actuals, Budget)
• Date/Period fields

Likely KPI Table if contains:

• Metric names (ARR, MRR, Churn, etc.)
• Quarter/Period identifiers
• Calculated ratios

Likely Master Data if contains:

• Names, Codes, IDs
• No amount fields
• Lookup/reference structure

Common Questions

"What's the difference between these tables?"

[Table A] appears to contain [type of data] while [Table B] contains [different type]. They're likely used for different purposes in your reporting.

"Which table should I use for [X]?"

For [X analysis], you'd typically want [Table Name] because it contains [relevant fields].

"How often is this updated?"

I can see data through [latest date]. The refresh schedule depends on your Datarails setup - typically daily or when data is loaded.

Follow-up Options

After exploration, offer relevant next steps:

• "Want me to analyze this data?"
• "Should I check for data quality issues?"
• "Ready to compare actuals to budget?"