Developing Story
Claude Code – Hardware-Software Co-Design via MCP (Emerging Workflow)
A developer demonstration shows Claude Code autonomously bridging SPICE circuit simulation and real oscilloscope hardware via MCP servers, representing an early but significant extension of AI coding agents into physical hardware co-design workflows. The pattern is generalizable across electronics engineering domains and expands the competitive scope of AI coding tools beyond pure software.
Importance: 62%Confidence: 70%Mentions: 1Updated: May 7, 2026
## Claude Code – Hardware-Software Co-Design via MCP
**Source:** Lucas Gerads personal blog (https://lucasgerads.com/blog/lecroy-mcp-spice-demo/)
### Overview
A developer demonstration has shown Claude Code being used to close the loop between SPICE circuit simulation and real oscilloscope hardware via Model Context Protocol (MCP) servers, according to the author's blog. The workflow reportedly allows Claude Code to autonomously run simulations, collect hardware measurements, and verify results — a novel application of AI coding agents to embedded systems and electronics engineering.
### Technical Architecture
According to the author, the system involves:
- An MCP server for a LeCroy oscilloscope (real hardware)
- An MCP server for a SPICE simulator (simulation environment)
- Claude Code acting as the orchestrating agent, closing the loop between predicted and measured behavior
### Significance
This demonstration is an early-stage but strategically significant indicator of AI agents moving from software-only environments into physical/hardware co-design workflows. The pattern — AI agent + simulation tool + physical instrument MCP servers — is generalizable to:
- RF and analog circuit design
- Power electronics verification
- PCB design and validation
- Broader test-and-measurement automation
This connects to existing tracked narratives around Claude Code's enterprise growth and Synera GmbH's agentic AI for industrial engineering workflows.
### Strategic Relevance
For technology firms and investors: the MCP ecosystem is enabling AI coding agents to extend beyond software into physical engineering domains. This expands the total addressable market for AI coding tools into EDA (electronic design automation), instrumentation, and industrial automation — sectors currently dominated by Cadence, Synopsys, and National Instruments/Keysight.
For legal practitioners: autonomous hardware-software co-design loops raise novel IP questions around AI-generated circuit designs, trade secret protection of simulation environments, and liability for hardware failures in AI-verified designs.