MCP Servers

Connect your tools and APIs to AI agents with MCP servers

Connect your APIs and third-party apps as MCP servers, so AI agents can move beyond 
answering questions to automating tasks across your product and external systems.

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Built for SaaS companies to create powerful, customer-facing AI agents.

Reduce integration complexity

The Model Context Protocol standardizes connections. Build once, share across all
your AI agents. No rework when adding new capabilities.

AI agents take real actions

Automate tasks across your product and third-party 
systems. Move beyond conversation to execution.

No vendor lock-in

You own your stack. Keep RAG on your cloud, wrap your APIs, 
bring your iPaaS, and connect any third-party MCP server.

Wrap your APIs

Connect your product features to AI agents

AI agents that can't control your product's features are just chatbots. Wrap your APIs as MCP servers so agents can execute actions: list_users, add_course, get_course_details. Build once, share across all agents. The standardized format means no rework as you add capabilities.

Pre-built integrations (Coming soon)

Meet users where they work, with pre-built integrations for Slack, MS Teams, and Twilio

Push messages or enable conversations in Slack, MSTeams, and Twilio (coming soon) without building integrations yourself. Guarantee AI agent adoption by meeting users in their existing workflows.

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RAG MCP

Connect your existing RAG system to keep sensitive data on your infrastructure

Connect your RAG system on AWS, Azure, or GCP as an MCP server. AI agents query your knowledge base without moving data to external platforms. Maintain data residency and compliance requirements while leveraging agent capabilities without sacrificing control.

Third-party app integrations

Connect iPaaS and orchestration systems as MCP servers

Re-use complex orchestration flows you've built in N8N, Make, or Workato. Connect any iPaaS or orchestration system as an MCP server so AI agents can trigger workflows when needed.

MCP Testing

Test MCP server architecture before deploying to users

Verify that your agent tools will work reliably before deploying to users. Test MCP server tools directly in the UI before and after deployment. View complete request/response logs and error messages to understand exactly what happens when agents perform actions. Catch and fix issues without burdening engineering. Ship AI agents with confidence.

Trusted by product teams.

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