A lightweight Model Context Protocol (MCP) server that runs inside your Kubernetes cluster, crawls your Services and endpoints via the Kubernetes API, auto-detects exposed OpenAPI specs, and builds a live, queryable index of your entire microservice surface area. It normalizes each spec (derefs, merges, fixes inconsistencies), tracks versions, and exposes the whole thing as MCP tools so agents can introspect, list, and invoke endpoints directly over in-cluster networking — essentially turning your microservices into a distributed, self-describing function registry.
Key Features
01Fetching and parsing of OpenAPI/Swagger specifications
02Embedded Apache Derby database for persistence (no external DB required)
03Configurable scheduled refresh of microservice data
04Exposure of type-safe tools via Model Context Protocol (MCP)
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06Automatic Discovery of services in Kubernetes namespaces
Use Cases
01Providing a standardized interface for external and internal tools to query and manage microservice APIs.
02Enabling AI agents and LLMs to discover and interact with internal Kubernetes microservices programmatically.
03Creating a dynamic, self-updating API registry for in-cluster service introspection.
04Facilitating automated testing and integration of microservices by allowing direct in-cluster endpoint invocation.
