Getting Started with Mutiny in Your AI Assistant

Once you’ve connected Mutiny to Claude or connected Mutiny to ChatGPT, you can start creating and managing customer-facing assets right away. Here are some common workflows.

Browse What’s Available

Start by exploring your workspace.

“Show me my Mutiny assets”
“What templates are available?”
“Show me what’s in my content library”

If you usually start from a blueprint in the Mutiny app, use a template here instead. Blueprints aren’t yet accessible in the MCP. Templates are created in the Mutiny app and then discoverable from conversation.

Create a Customer-Facing Asset

Create any type of asset, the more context you provide, the more personalized the result.

“Create a proposal for Acme Corp using the pricing proposal template”
“Build a 1:1 landing page for Stripe. They’re a fintech company focused on payment infrastructure”
“Create a case study about how we helped Snowflake increase pipeline by 40%”
“Make a meeting recap for my call with the Databricks team”

Use Your Own Research and Data

The most powerful workflow: combine research already in your conversation with Mutiny’s asset creation.

“Tell me about Acme Corp. What do they do, who are their competitors?”
“Now create a landing page for Acme Corp using that research, with the 1:1 ABM template”
“Update the headline to focus on their cloud migration initiative”
“Publish the Acme Corp landing page”

Manage Your Content Library

“Upload this logo to my library: https://example.com/acme-logo.png ”
“Tag my Snowflake case study with ‘data-cloud’ and ‘enterprise’”
“Show me all library items tagged ‘competitor’”

“Publish my Acme Corp proposal”
“What’s the URL for my published Stripe landing page?”

Tips

Be specific: include the account name, asset type, and personalization details
Combine with research: the more context in your conversation, the better the output
Iterate: refine content after initial creation with follow-up messages

What Can You Do with Mutiny + AI?

Mutiny + Model Context Protocol (MCP)