MCP Gateway & Registry

Unla is a lightweight, configuration‑driven gateway that turns any existing MCP Server or RESTful API into a fully compliant MCP endpoint without touching your application code. By acting as an intermediary, it translates legacy request/response patterns into the Model Context Protocol’s standardized stream‑based format, allowing AI assistants such as Claude to interact seamlessly with services that were never designed for MCP. This eliminates the need for custom adapters, reduces maintenance overhead, and accelerates time‑to‑market for AI‑enabled applications.

The core value of Unla lies in its zero‑intrusion design. It can be deployed on bare metal, virtual machines, ECS, Kubernetes clusters, or any cloud provider that supports Docker. Once running, a simple YAML configuration file describes the target API’s endpoints, authentication, and data mapping. Unla then exposes those operations as MCP resources, complete with SSE streams, message endpoints, and streamable HTTP routes. Developers can manage the gateway through an intuitive web UI that handles server discovery, health checks, and logging—all without writing a single line of code.

Key capabilities include:

• Automatic protocol conversion – Legacy JSON or XML responses are wrapped into MCP context messages, preserving metadata and enabling fine‑grained control over token limits.
• Secure authentication integration – Supports JWT, OAuth2, and custom headers out of the box, ensuring that only authorized clients can access protected resources.
• Scalable streaming – Leverages Server‑Sent Events (SSE) and HTTP/2 streams to deliver real‑time data with low latency, ideal for conversational AI workflows.
• Extensible resource mapping – Users can define multiple MCP resources per backend service, each with its own sampling and prompt templates.
• Built‑in monitoring – The dashboard exposes metrics, logs, and health checks, simplifying observability in production environments.

Typical use cases span from rapid prototyping of AI assistants that need to query legacy business systems, to enterprise‑grade integrations where a single gateway exposes dozens of internal services to a unified AI layer. For example, a customer support bot can query an old ticketing API through Unla, receive structured context objects, and generate natural language responses without modifying the ticketing backend. Similarly, data analytics pipelines can expose historical datasets as MCP streams, enabling AI agents to perform on‑the‑fly analysis and reporting.

In short, Unla removes the friction between existing services and the MCP ecosystem. By offering a plug‑and‑play gateway that requires only configuration, it empowers developers to focus on building intelligent experiences rather than wrestling with protocol mismatches.