Imports and data migration · Fieldproxy MCP
Bring the spreadsheet in, by asking
From Claude, ChatGPT or Copilot in Teams, on your live field service data, with a confirm step before anything changes.
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Illustration of Fieldproxy's MCP tools inside Claude, ChatGPT and Copilot. Names and data are examples.
Short answer
Imports and data migration from ChatGPT, Claude or Copilot: how does it work?
Through Fieldproxy's MCP server, Claude, ChatGPT or Copilot can read an export or spreadsheet, match its columns to your tables, add a field where the data needs one, and import the rows. The import is dry-run first, showing what would be added, what would be updated and which rows it flagged; where the table has an import profile, existing rows are updated instead of duplicated. It is applied only when you confirm and can be undone. Up to 1,000 rows go in per confirmed change.
Last verified September 27, 2026
Real requests
What people ask, and the tools it calls
| You ask | Fieldproxy tools | You get |
|---|---|---|
| “Import this spreadsheet of 400 new sites for Northwind” | describe_schema, import_records, confirm_write | The rows mapped to your sites table, imported on confirm |
| “Here is our Jobber client export, bring the customers and properties in” | describe_schema, import_records, confirm_write | Customers and properties mapped and imported, matched rows updated instead of duplicated |
| “The export has a gate code column we don't have, add it and fill it in” | add_column, import_records | A new field, filled from the file |
| “Which of the imported customers have no email or phone?” | run_sql | The gaps to fix before you go live |
| “Restore the 12 jobs someone deleted this morning” | list_deleted_records, restore_deleted_records | The jobs back, on confirm |
| “Export every open job to CSV for the auditor” | export_csv | A CSV file |
The part nobody else does
Your AI can change the software, not just the data
Every other field service connector we checked (September 27, 2026) reads records and, at most, edits a few of them. Fieldproxy's MCP server can also build: new fields, screens, tables, automations and agents, made in a sandbox copy of your workspace and live only when you approve.
Add a field
Build a screen
Wire an automation
Create an agent
Add your own tools
Roll back anything
Read more: customise field service software with AI · build it with Claude or ChatGPT instead?
Guardrails
Your AI proposes. A person confirms.
Built for operations with branches, teams and an IT review, not a single login.
Nothing changes on one call
Every write, send or action is a proposal the user confirms within 30 minutes. Writes can be undone. More than 5 rows needs bulk permission, and more than 1,000 is refused.
Keys scoped like API keys
Limit a key to certain tables, certain rows ("only the North region's jobs"), hidden columns, insert/update/delete, and an expiry from 1 hour to 90 days. Postgres enforces the row limits.
Builds save as drafts
Apps and automations are checked against the database before they save, new automations and agents are saved switched off, and public apps are never changed.
Sends are limited
Email goes only from the user's own mailbox, at most 20 sends an hour per key, inside the workspace's quiet hours. A sandbox never sends.
Everything is logged
Every call is written to an audit log with the tool, key, person and outcome. Administrators see every key and connected app, and revoking one applies on the next request.
FAQ
Questions
- How many rows can it import at once?
- Up to 1,000 rows per confirmed change, so a larger file goes in as several batches, each dry-run and confirmed.
- Can it add a field my data needs?
- Yes, for an administrator on a workspace with build switched on: it adds the column first, then imports into it.
- Can an import be undone?
- Yes. The import is one applied change with an undo, and deleted records can be restored.
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