💬 Feedback & Feature Requests: Supercharging OpenROAD with an AI-Powered MCP Server 🤖

[luarss]

Hey everyone,

We're exploring the integration of a Model Context Protocol (MCP) server to bring powerful AI-driven capabilities to OpenROAD. The vision is to create an "AI assistant" that can understand our tools, automate complex tasks, and help you achieve better PPA (Power, Performance, and Area) with less effort.

To ensure we build something that is truly useful for the OpenROAD community, we need your expertise and feedback. We want to know where an AI assistant could have the most impact on your day-to-day work.

Our guiding question is:

What are the most time-consuming, repetitive, or challenging parts of your physical design workflow that you wish an AI could simplify or automate?

To help structure the conversation, we've broken this down into a few key areas. Please feel free to add your thoughts on any or all of these topics.

---

🛠️ AI for Flow Automation & Tool Orchestration

How can an AI assistant make the OpenROAD flow more intelligent and easier to manage?

• Intelligent Flow Recipes: Would you use an AI that could suggest an optimal flow or a set of tool parameters based on your design's characteristics (e.g., "Give me a good starting recipe for a high-performance, low-power IoT design on SKY130")?
• Automated Debugging: If a run fails, what information would you want an AI to automatically gather and summarize for you? (e.g., "Summarize the critical path timing violations from the last run and point to the relevant lines in the log files").
• Natural Language Commands: What are some of the tcl commands you use most often that you would rather express in plain English? (e.g., "Show me the top 10 worst timing paths" or "What's the current routing congestion?").

---

🧠 AI for Design Space Exploration & PPA Optimization

How can we leverage AI to explore the vast design space more effectively and achieve better results?

• PPA Trade-offs: Would you be interested in an AI that could help you explore PPA trade-offs? (e.g., "Show me how the clock frequency impacts power consumption for this block" or "Find the floorplan that gives me the best balance of area and timing").
• "What-if" Scenarios: What kind of "what-if" analyses would be most helpful? (e.g., "What if I add another 100 flip-flops to this module? How would that impact the overall timing and routability?").
• Visual Analysis: How could an AI help you better understand and visualize your design in the OpenROAD GUI? (e.g., "Highlight all the cells on the critical path" or "Show me a heatmap of the areas with the highest routing congestion").

---

🔌 AI for Integrating with the Broader EDA Ecosystem

How can an AI assistant help OpenROAD work more seamlessly with other tools and platforms?

• Connecting to Simulators: Could an AI help bridge the gap between OpenROAD and simulation tools? (e.g., "Run a gate-level simulation of the critical path and report the results").
• Version Control Integration: What kind of interactions with Git would be most useful? (e.g., "Compare the PPA results between the current branch and the main branch" or "Find the commit that introduced this timing violation").
• Documentation & Reporting: What kind of reports or documentation would you want an AI to generate automatically? (e.g., "Create a summary of the final PPA results for this design, including key metrics and screenshots of the layout").

---

✨ Your "Blue Sky" Ideas for an AI-Powered OpenROAD

If you could give an AI assistant for OpenROAD any superpower, what would it be? No idea is too ambitious!

We are incredibly excited about the potential of AI to democratize hardware design and further the mission of OpenROAD. Your feedback will be invaluable in shaping the future of this project.

Thanks for your contributions!

[Pavankumar07s]

Hi @luarss team,

Super excited about the MCP server idea — AI + OpenROAD has huge potential for flow tuning, debugging, and PPA exploration.

I'm planning to apply for the GSoC 2026 project "OpenROAD-MCP Docker Deployment and Cross-Platform Support with Production-Ready Testing and QA".

Current status looks perfect for this:

• https://github.com/luarss/openroad-mcp has solid foundation (uv, tests, PTY sessions)
• Production Docker + GHCR + Windows/WSL2 + deep ORFS integration tests + load/memory profiling are still WIP

Questions to clarify scope:

1. Preferred base image? (python:3.13-slim-bookworm, ubuntu:24.04, or ORFS base?)
2. Target ORFS flows for integration tests? (sky130/gf180, nangate45, at least 5–8 designs?)
3. Load target: 50 concurrent sessions realistic? Any preferred tool (locust, k6, custom asyncio)?
4. Memory profiling: valgrind + pytest-memray, or something else?

In parallel, I plan to start with:

• Multi-stage production Dockerfile (size <400 MB, non-root)
• GHCR publish workflow (multi-arch amd64/arm64)

Happy to discuss / take feedback before proposal. Would love to contribute early PRs if mentors are open.

Thanks!
Pavan

[luarss]

Questions to clarify scope: 1. Preferred base image? (python:3.13-slim-bookworm, ubuntu:24.04, or ORFS base?) - ORFS base image + UV 2. Target ORFS flows for integration tests? (sky130/gf180, nangate45, at least 5–8 designs?) - Simple platforms like nangate45, asap7. Small designs like GCD 3. Load target: 50 concurrent sessions realistic? Any preferred tool (locust, k6, custom asyncio)? Leave it up to you. This should be simulated on a single machine as well. 4. Memory profiling: valgrind + pytest-memray, or something else? Something python-based will be good enough. The priority is on getting something working, we can optimise using valgrind later on. Best, Jack

…

On Fri, Mar 6, 2026 at 2:52 AM Pavan kumar ***@***.***> wrote: Hi @luarss <https://github.com/luarss> team, Super excited about the MCP server idea — AI + OpenROAD has huge potential for flow tuning, debugging, and PPA exploration. I'm planning to apply for the GSoC 2026 project "OpenROAD-MCP Docker Deployment and Cross-Platform Support with Production-Ready Testing and QA". Current status looks perfect for this: - https://github.com/luarss/openroad-mcp has solid foundation (uv, tests, PTY sessions) - Production Docker + GHCR + Windows/WSL2 + deep ORFS integration tests + load/memory profiling are still WIP Questions to clarify scope: 1. Preferred base image? (python:3.13-slim-bookworm, ubuntu:24.04, or ORFS base?) 2. Target ORFS flows for integration tests? (sky130/gf180, nangate45, at least 5–8 designs?) 3. Load target: 50 concurrent sessions realistic? Any preferred tool (locust, k6, custom asyncio)? 4. Memory profiling: valgrind + pytest-memray, or something else? In parallel, I plan to start with: - Multi-stage production Dockerfile (size <400 MB, non-root) - GHCR publish workflow (multi-arch amd64/arm64) Happy to discuss / take feedback before proposal. Would love to contribute early PRs if mentors are open. Thanks! Pavan — Reply to this email directly, view it on GitHub <#7861 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AJOOEP5PSS4ZJTNKRXNDZF34PHEG5AVCNFSM6AAAAACWITRTA2VHI2DSMVQWIX3LMV43URDJONRXK43TNFXW4Q3PNVWWK3TUHMYTMMBRGQYTCMQ> . You are receiving this because you were mentioned.Message ID: <The-OpenROAD-Project/OpenROAD/repo-discussions/7861/comments/16014112@ github.com>