OpenRPC MCP Server

Overview

The OpenRPC MCP Server bridges the gap between AI assistants and existing JSON‑RPC services by exposing a simple, standardized interface. Instead of writing custom adapters for each remote procedure call endpoint, developers can leverage this server to query any JSON‑RPC API through a single, well‑defined toolset. This dramatically reduces integration time and eliminates the need to maintain separate connectors for each service.

What It Solves

Modern applications frequently rely on legacy or third‑party services that expose functionality via JSON‑RPC. AI assistants, however, expect to interact with structured tools or prompts defined in MCP. The OpenRPC server translates these expectations into concrete RPC calls, allowing assistants to invoke remote procedures as if they were native tools. This solves the problem of heterogeneous API integration—developers no longer need to write bespoke wrappers for every service they wish to expose.

Core Functionality

• : A versatile tool that accepts a target server URL, the method name to invoke, and any parameters required. The result is returned in JSON format, making it easy for the assistant to parse and use.
• : Leverages OpenRPC’s specification to automatically enumerate all available methods on a given server. This tool provides introspection capabilities, enabling assistants to understand what operations are possible before attempting a call.

Both tools are designed for zero‑configuration use: the only inputs required are the endpoint details and method names, allowing AI assistants to perform complex remote interactions without prior knowledge of the underlying service.

Use Cases & Real‑World Scenarios

• Enterprise Automation: An AI assistant can trigger business workflows (e.g., order processing, inventory checks) by calling internal JSON‑RPC services.
• DevOps Operations: Automate infrastructure tasks such as scaling, health checks, or configuration changes through RPC calls triggered by natural language commands.
• Data Retrieval: Fetch structured data from legacy systems (CRM, ERP) and present it in conversational form, eliminating the need for custom data pipelines.
• Rapid Prototyping: Developers can expose new APIs quickly to the assistant, test interactions in real time, and iterate without rebuilding tooling.

Integration with AI Workflows

The server plugs directly into the MCP ecosystem, meaning any assistant that understands MCP can treat and as first‑class tools. Developers simply add the server configuration to their assistant’s runtime, and from there the assistant can:

1. Discover available methods with .
2. Invoke the desired method using , passing parameters derived from user intent or context.
3. Process the JSON response, optionally feeding it back into prompts for richer conversational output.

Because communication occurs over standard input/output streams, the server can be launched as a lightweight process, scaled horizontally, or even embedded in containerized environments.

Unique Advantages

• Standardization: By adhering to the OpenRPC specification, the server guarantees compatibility across a wide range of JSON‑RPC services without custom adapters.
• Dynamic Introspection: provides live method listings, enabling assistants to adapt to evolving APIs on the fly.
• Simplicity: The minimal configuration required (just a server URL and method name) reduces friction for developers, allowing rapid experimentation.
• Extensibility: The MCP framework allows additional tools or prompts to be added in the future, ensuring that the server can grow alongside evolving AI workflows.

In summary, the OpenRPC MCP Server empowers developers to expose any JSON‑RPC endpoint as a first‑class tool for AI assistants, streamlining integration, enhancing automation capabilities, and accelerating the delivery of intelligent, context‑aware applications.