Ethereum RPC MPC Server

Overview

The Ethereum RPC MPC Server is a lightweight, TypeScript‑based Model Context Protocol (MCP) implementation that exposes the full Ethereum JSON‑RPC API to AI assistants such as Claude or Cursor. By acting as a bridge between an AI model and the Ethereum blockchain, it removes the need for developers to write custom connectors or SDK wrappers. The server accepts standard JSON‑RPC requests and forwards them to a specified Ethereum node, returning the raw blockchain data in a format that MCP clients can consume directly. This seamless integration enables AI assistants to answer questions about on‑chain state, execute transactions, and monitor contract activity without any additional plumbing.

Why it matters for AI‑powered development

AI assistants often require real‑time data from external sources to provide accurate responses. For blockchain projects, the most common source is the Ethereum node RPC interface. Traditionally developers would have to expose these endpoints securely, manage authentication, and format responses for the assistant. The Ethereum RPC MPC Server consolidates all of this into a single, standardized MCP service. It supports any chain that offers JSON‑RPC, and it automatically activates Zircuit‑specific methods when connected to a Zircuit endpoint. This eliminates boilerplate, reduces latency, and guarantees that the assistant receives data in a consistent structure.

Key capabilities

• Full JSON‑RPC support – All standard Ethereum methods (, , , etc.) are available through a single MCP resource.
• Chain‑agnostic configuration – Provide any RPC URL and optional chain name; the server defaults to a reliable public endpoint if none is supplied.
• Zircuit SLS integration – When connected to a Zircuit node, the server unlocks specialized quarantine queries (, ) that are invaluable for security audits and compliance monitoring.
• Analytics middleware – Optional SQLite‑based analytics capture request counts, durations, and errors, giving developers visibility into usage patterns without exposing sensitive data.
• Future‑ready – Planned support for indexed APIs will allow more efficient historical queries and complex on‑chain analytics, expanding the server’s utility beyond basic RPC.

Real‑world use cases

• Smart contract analysis – An AI assistant can ask whether a given address is a contract, what ABI it implements, or retrieve its bytecode.
• Portfolio monitoring – Developers can query balances for multiple addresses, track token holdings, and generate real‑time reports.
• Transaction monitoring – With Zircuit support, security teams can have the assistant flag quarantined transactions or audit transaction flows automatically.
• Educational tools – Students and hobbyists can interact with the blockchain through conversational prompts, learning how RPC calls map to on‑chain data.
• CI/CD pipelines – Automated tests can invoke the server via MCP to validate contract deployments, state changes, and event logs as part of a continuous integration workflow.

Integration with AI workflows

Adding the server to an MCP client is as simple as registering a new command or executable with the desired RPC URL. Once configured, AI assistants can issue natural‑language queries that are translated into JSON‑RPC calls behind the scenes. The responses are returned in a structured format that the model can parse, enabling it to generate precise answers or even propose code snippets based on live blockchain data. Because the server conforms to MCP standards, it works seamlessly with any assistant that supports the protocol, making it a drop‑in solution for developers looking to fuse AI reasoning with decentralized data.