About windsor-ai-business-data
A skill for retrieving business data through Windsor.ai connectors, for developers and analysts building dashboards, reports, or integrations. Its workflow covers connector discovery, field exploration, metadata lookup, and data queries.
Key features
- 01Access data through 325+ connectors
- 02Discover connected platforms and accounts
- 03Explore fields and query options
- 04Inspect field metadata
- 05Retrieve filtered data by date range
Use cases
- 01Preparing data for dashboards and reports
- 02Analyzing ad and campaign metrics
- 03Loading CRM or ecommerce data into code
- 04Seeding prototypes with real data
MCP support
Windsor.ai exposes four MCP tools: get_connectors, get_options, get_fields, and get_data. They support discovering accounts and fields, inspecting schemas, and retrieving business data.
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ cline/ skills --skill windsor-ai-business-dataAfter installing, type/windsor-ai-business-datain Claude Code to confirm it loaded.
Details
From the project READMEWindsor.ai Business Data Skill
Use this skill whenever the user needs business data — marketing analytics, sales metrics, CRM data, ecommerce transactions, financial data, or any other data available through Windsor.ai's 325+ connectors.
When to Use
- User is building a dashboard, report, or data visualization that needs business data from any source
- User asks about ad spend, campaign performance, ROAS, CTR, CPC, or conversion metrics
- User needs CRM, sales, ecommerce, or financial data in their codebase
- User needs to explore what data sources or fields are available
- User wants to seed a project with real data (e.g. for testing, prototyping, or generating fixtures)
- User is building an integration with any platform supported by Windsor.ai
Available Tools
Windsor.ai provides 4 MCP tools:
get_connectors
Lists all connected platforms and their account IDs. Always call this first if you don't know what accounts are available.
get_options
Returns available fields, date filters, and options for a specific connector. Use this to discover what data can be queried before calling get_data.
Parameters:
connector(required): Platform ID like"google_ads","facebook","tiktok","linkedin","googleanalytics4","hubspot","salesforce","searchconsole","instagram","youtube","google_my_business","shopify","stripe","quickbooks", and 300+ moreaccounts(required): List of account IDs fromget_connectors
get_fields
Returns detailed metadata about specific fields — data types, descriptions, available values. Use this when you need to understand the schema before writing code that processes the data.
Parameters:
connector(required): Platform IDfields(required): List of field IDs like["campaign", "spend", "clicks"]
get_data
Retrieves actual data. This is the main query tool.
Parameters:
connector(required): Platform IDaccounts(required): List of account IDsfields(required): Fields to retrieve, e.g.["campaign", "date", "spend", "clicks", "impressions"]date_from/date_to: Date range as"YYYY-MM-DD"date_preset: Shorthand like"last_7d","last_30d","this_month","last_3m"filters: Conditions like[["spend", "gt", 100], "and", ["campaign", "contains", "Sale"]]options: Connector-specific options like{"attribution_window": "7d_view,1d_click"}
Workflow Pattern
- Discover → Call
get_connectorsto see what's connected - Explore → Call
get_optionsto see available fields for a connector - Understand → Call
get_fieldsfor field metadata if building typed interfaces - Query → Call
get_datato pull the actual data
Common Field Patterns
Fields vary by connector type. Here are some common examples:
Marketing/Ads connectors: campaign, adgroup, ad, date, device, country, spend, clicks, impressions, conversions, revenue, ctr, cpc, cpm, roas
CRM connectors: deal, contact, company, stage, owner, amount, close_date
Ecommerce connectors: order_id, product, quantity, price, customer, status
Always check get_options first since available fields vary by connector.
Tips
- When building dashboards or charts, pull data with
get_dataand write it to a local JSON/CSV file the app can read - For TypeScript projects, use
get_fieldsto generate accurate type definitions - Use
date_presetfor quick queries:"last_7d","last_30d","this_month" - Combine filters for focused queries:
[["spend", "gt", 0], "and", ["campaign", "ncontains", "test"]] - You can join data from different connectors (e.g. ad spend + CRM revenue) by pulling from each and merging in code