Moleculer MCP Bridge – Overview

The Moleculer MCP Bridge is a lightweight gateway that exposes every action of your Moleculer.js microservices as tools in the Model Context Protocol (MCP). It solves a common pain point for AI‑centric development: connecting an AI assistant to a complex, event‑driven service mesh without writing custom adapters. By turning each Moleculer action into an MCP tool automatically, developers can give Claude or other AI agents direct access to business logic, data stores, and orchestrated workflows already present in their Node.js microservice architecture.

At its core, the bridge listens on a configurable HTTP port and serves an MCP endpoint. It introspects the running Moleculer broker, applies a whitelist of action patterns (e.g., , ), and generates MCP tool definitions that mirror the original service signatures. The resulting tools include descriptive names, parameter schemas derived from Moleculer’s validation rules, and optional default values. This means an AI assistant can request a user list with pagination or trigger complex business flows just by invoking the exposed tool, while the bridge handles serialization, authentication (via Moleculer’s built‑in security), and error translation.

Key capabilities include:

• Automatic tool discovery – No manual mapping needed; the bridge scans all registered services and exposes them on demand.
• Fine‑grained control – A simple JSON config allows whitelisting, custom tool names, parameter overrides, and server settings such as port or broker configuration file.
• Seamless integration – Once the MCP endpoint is reachable, any AI client that supports MCP (Claude Desktop, LangChain, etc.) can be pointed at the bridge and immediately gain access to all microservice actions.
• Extensibility – The bridge can be started with default settings for quick prototyping or with a full Moleculer configuration file to hook into production brokers, NATS clusters, or custom transport layers.

Typical use cases include:

• Rapid prototyping – Developers can expose new services to an AI assistant on the fly, enabling quick experimentation and feedback loops.
• Hybrid automation – AI agents can orchestrate microservice calls, gather data, and return results to users in a single conversation.
• Operational monitoring – Exposing health checks or metrics as MCP tools lets an assistant query system status without additional tooling.
• Multi‑tenant service layers – By filtering actions per tenant, the bridge can provide scoped toolsets to different AI agents or user groups.

In summary, the Moleculer MCP Bridge turns a mature Node.js microservice ecosystem into an instantly usable AI toolset, eliminating the need for bespoke adapters and allowing developers to focus on business logic while leveraging advanced AI workflows.