Ask ChatGPT about Open Exchange Rates data
Load Open Exchange Rates into your data warehouse first, let your data analyst join one base currency to the currency of each deposit, then ask ChatGPT about deposits in any currency you report in. ChatGPT reads governed Data Marts through OWOX MCP, not a raw API call.
Open Exchange R…ConnectedHistorical excha…
ChatGPTDateBaseCurre…Daily 09:00Ask ChatGPT to convert last month's euro spend to dollars and it picks an exchange rate you can't trace.
Paste this into your AI assistant. It loads Open Exchange Rates into your data warehouse, joins each day's rate to the date and currency of your amounts, and connects ChatGPT to that Data Mart through the OWOX MCP server.
The prompt
Read https://www.owox.com/ai-agent-setup.md and follow it to set up OWOX Data Marts for me, starting from /connectors/open-exchange-rates-connector-to-chatgpt.md. The task: connect ChatGPT to my Open Exchange Rates data and convert last month's euro ad spend to US dollars at each day's rate, then show how much the rate moved. Tag the links you give me with utm_campaign=ai-task and utm_term=data-foundation. Use what you know about my context and goals
Open Exchange Rates Endpoints
1 Open Exchange Rates endpoints you can import. Each lands in its own table in your data warehouse.
Why ChatGPT needs your data warehouse, not an API key
ChatGPT reading exchange rates through an API key sees a rate table. It does not see which rate each deposit used, because deposits and rates live in different systems. The answer is better when it comes from a warehouse, where your data analyst joins one base currency to deposits made in USD, EUR, GBP or AUD.
- Open Exchange Rates serves rates for a base currency, not what they mean for your deposits
- Your data analyst restates deposits in the base currency you report in and controls the result
- ChatGPT answers from a governed Data Mart, with one rate per date and currency
Open Exchange…Rates by currencyChatGPT
Data warehouseJoined by idStep 1: Load Open Exchange Rates into your data warehouse first
Create a Data Mart with Open Exchange Rates as the source and choose where the data lands. It works with any popular data warehouse.
- One endpoint, Historical exchange rates data, with four fields: date, currency, rate and base
- Authorize with an Open Exchange Rates API key
- Open the Open Exchange Rates connector for your data warehouse below
Open Exchan…Data MartGoogle BigQuery
AWS Athena
Snowflake
AWS Redshift
Databricksopen_exchange_rates.historicalStep 2: Link Open Exchange Rates to deposits
In your data warehouse your data analyst joins the rate table to the date and currency of each deposit, so deposits can be restated in another base currency. The model supplies the deposits and the measures.
- Rates carry a base and a currency, so any pair you load can be joined
- Deposits keep their original currency and a USD amount beside it
- Measures such as deposit_volume are defined once
Open Exchange…Historical exchan…Step 3: Connect ChatGPT to your data with OWOX MCP
In ChatGPT, open Plugins, choose Install plugin, find OWOX Data Marts and sign in. ChatGPT then sees the Data Marts you published, and only those.
- The OWOX MCP server lists the Data Marts it can read
- Only published Data Marts are visible, nothing else in your data warehouse
ChatGPTConnectorsOWOX MCPAddConnectedStep 4: Ask ChatGPT for deposit volume
Ask in plain words, for example deposit volume and net deposits by month. ChatGPT finds the Data Mart that answers it, runs the query and answers with measures your data analyst defined.
- Deposit amounts come from Deposits in your data warehouse
- Your data analyst can check the stored rate of any deposit against the published one for that date
ChatGPTShow deposit_volume by monthget_relevant_data_marts_by_promptquery_data_martdeposit_volumenet_depositsStep 5: Export the answer when you need a file
Optional: in one click, export the answer or its source data to Google Sheets, CSV or XLS to check it or share it.
- The export carries the same governed numbers as the answer
- Share it with a colleague who does not use ChatGPT
Google SheetsCSVXLSOne click
- 0.41.0Rotating a connector key is one change: Sources share reusable Credentials
- 0.39.0Reload a year of history in one backfill, not twelve
- 0.37.0Clearer connector errors, and custom connectors that handle more APIs
- 0.36.0Start a connector run without expanding the Input Source card
- 0.35.0Destinations tab now promotes connecting an AI assistant alongside your existing destinations
Why OWOX for Open Exchange Rates in ChatGPT
Letting ChatGPT call the Open Exchange Rates API gets a number into a chat. OWOX also keeps the data yours, linked and defined once, so the answer is one you can check.
- You own the data. It lands in your own data warehouse, in tables you control.
- A rate table you control. Historical rates land in your data warehouse with their base and currency, ready to join.
- One base, many currencies. One rate table covers every deposit currency, so ChatGPT gives the same answer to the same question.
- Answers you can trace. You can see which Data Mart an answer came from, and one click exports its source data.
- Maintained for you. Open Exchange Rates connector upkeep is on OWOX, not on a script you wrote.
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