Noodle Seed provides a runtime platform to connect existing software APIs and MCP servers to AI agents while managing identity, credentials, rate limits, and audit logs.
What the product does and how it is positioned
Noodle Seed is a cloud runtime designed to turn existing software workflows and APIs into conversational experiences for AI agents and embedded assistants.
The platform governs agent access by brokering credentials, enforcing role and tenant boundaries, and maintaining operational audit logs across agent interactions.
Source-supported ways to use the product
Implementing conversational discovery and booking workflows that connect customer requests to booking APIs.
Handling customer inquiries through conversational interfaces connected to backend systems.
Managing internal employee inquiries and support requests using embedded assistants.
The documented workflow, where available
Link existing products, APIs, or MCP servers to the runtime while isolating credentials and secrets from agents.
Establish customer, tenant, role, and permission boundaries alongside surface-specific policies and rate limits.
Monitor runtime health, track usage and failures, and add new agents or surfaces without additional platform code.
Review audit records of deployments, rollbacks, and policy denials generated without exposing tokens or request bodies.
Noodle Seed acts as an intermediary layer between AI agents and underlying product APIs. The runtime maintains identity and access controls by holding brokered credentials and secrets, helping reduce external agents from receiving raw credentials directly.
Operational controls and governance ship with the platform, allowing teams to scope rate limits and policy boundaries by tenant, role, and client surface. Observability tools track runtime health and error rates across connected deployments.
Checks to run with your own material and workflow
What was checked and when
Answers based on the source-checked product record
The platform connects existing software backends, APIs, and MCP servers to conversational agent surfaces such as ChatGPT, Claude, Copilot, Gemini, and MCP clients.
Brokered credentials and secrets remain secured within the runtime environment and are not exposed directly to the AI agent or client.
Audit events record deployments, rollbacks, operator actions, and policy denials while deliberately excluding request bodies and access tokens.
The platform supports workflows where users can generate preliminary drafts or progress before signing in, after which the session carries over into the authenticated product.
The platform documentation explicitly references adherence to SOC II and GDPR compliance standards.
