ChatGPT Integration
ChatGPT + Diaphora
Use Diaphora as the structured workflow engine and ChatGPT as the collaborative surface for refining the final narrative.
Overview
How the ChatGPT workflow fits
The ChatGPT integration pattern is about handoff. Diaphora gathers, structures, and renders the result; ChatGPT becomes the conversational layer teams use to adapt that output into an email, memo, strategy note, or stakeholder brief.
ChatGPT works best when it starts from clean inputs. Diaphora produces those inputs by gathering data, validating structure, and rendering a first-pass document. ChatGPT then helps the user reshape that output for the audience in front of them.
Instead of asking ChatGPT to do the whole workflow from scratch, teams let Diaphora do the deterministic system work and reserve ChatGPT for the final editorial, brainstorming, and audience adaptation step.
Setup
How to integrate ChatGPT with Diaphora
Diaphora is exposed as an MCP server. The setup flow is intentionally lightweight: you need a Diaphora account, then you add Diaphora as a custom connector inside ChatGPT.
1. Start with a Diaphora account
Make sure you have an active Diaphora account before configuring ChatGPT. That account is the identity layer ChatGPT will connect through.
2. Open ChatGPT and add a custom connector
Inside ChatGPT, add Diaphora as a custom MCP connector. This points ChatGPT at Diaphora's MCP surface instead of treating the workflow as a pasted prompt.
3. Complete the Diaphora IAM login flow
When ChatGPT initiates the connection, you will be redirected into the Diaphora IAM login process. Authenticate there to authorize the connector.
4. Return to ChatGPT and start using Diaphora tools
Once the IAM flow is complete, ChatGPT can access Diaphora as an MCP server and use connected plans and workflows as part of your working session.
How it works
Working with the integration
1. Run the deterministic workflow in Diaphora
Start in Diaphora when the job needs connector access, repeatable extraction, or schema-shaped output.
- Diaphora gathers the operational context from the right tools.
- The plan enforces structure before any final narrative layer is added.
2. Use the rendered document as your base draft
If the plan returns a document, that document is the ideal starting point for ChatGPT. It already captures the core facts, structure, and recommended framing.
- This reduces prompt thrash and cuts down on missing context.
- The team starts from a finished artifact instead of a blank box.
3. Ask ChatGPT to adapt, not reconstruct
ChatGPT is best used to translate the Diaphora output for a specific audience or purpose: a board memo, customer email, strategy note, or internal summary.
- Ask for style shifts, condensation, expansion, or alternate framings.
- Keep the factual backbone anchored to the original Diaphora output.
4. Keep Diaphora as the source of truth
When the underlying facts change, rerun the plan in Diaphora rather than manually rebuilding the context in ChatGPT.
- This preserves repeatability across every refresh.
- ChatGPT stays focused on collaboration instead of data wrangling.