How to connect AI assistants to hardware repos using MCP

The problem with unzipping reference designs

Hardware engineers waste too much time hunting down past design decisions. You know you routed an nRF52840 layout three projects ago, but the project sits inside a zip file on a shared drive. Finding the exact decoupling capacitor values or antenna matching layout means downloading the archive, booting up KiCad or Altium, and clicking through sheets. Standard AI models cannot help you here either. Large language models hallucinate pinouts because raw schematic files and Gerber zips are unstructured noise to a standard chat window.

Hardware repos need structured web endpoints. BoardRepo tackles the rendering side by taking native KiCad and Altium files and serving interactive 3D models, copper layers, schematics, and bill of materials tables directly in the browser. But manual visual checks still require human effort. To automate hardware lookups, you need a protocol that lets an AI client query schematic symbols, component parts, and netlists programmatically.

How Model Context Protocol bridges local AI and hardware data

Model Context Protocol (MCP) solves the context retrieval problem. Instead of pasting 50,000 lines of XML or raw schematic text into a prompt window, MCP provides a structured contract. Your local AI assistant talks to an MCP server, issuing standard queries for project files, board revisions, and component details. The MCP server reads the parsed project structure from the host and returns precise JSON payloads.

BoardRepo includes an MCP server integration out of the box. This endpoint exposes hosted KiCad and Altium repository data directly to compliant assistants. When you ask your client to find a specific microcontroller layout or check a component value, the assistant calls the MCP tool, scans your hosted projects, and pulls back real source data instead of guessing.

Configuring your assistant to query hosted repos

Setting up an MCP connection requires point-to-point configuration between your AI desktop client and the remote host. You point your assistant config file to the target MCP endpoint. The server exposes tools for searching project indexes, inspecting schematic files, and extracting component records.

As detailed in BuiltToWinWeb's guide on deploying AI agent discovery files and MCP servers, exposing structured interfaces on web domains requires clean transport protocols and clear endpoint definitions. Once configured, your assistant queries the server seamlessly in the background during active design sessions.

For example, you can query a hosted KiCad board with direct prompts:

• Find reference designs: Ask your client to locate a project containing an nRF52840 example in the repository.
• Audit components: Ask for a summary of regulator part numbers across version 2 of your hosted boards.
• Extract assembly data: Ask for specific bill of materials lines from a published board like OtterCastAudioV2 without opening a spreadsheet.

Querying schematics, BOMs, and footprints

Why does this matter to practicing engineers? Because local EDA searches are traditionally slow. If you want to check whether an old revision used a 0402 or 0603 footprint for a feedback resistor, opening the layout application takes minutes. With an MCP server hooked into your web repository, the query returns in seconds.

1. Reference design retrieval

When starting a new schematic, board designers rely heavily on proven sub-circuits. Instead of rebuilding USB-C protection or switching converter layouts from scratch, you query your hosted projects. The AI assistant uses the MCP integration to inspect schematic nets across prior hardware revisions, confirming component values and part numbers before you draw the first wire.

2. Automated BOM audits

Component errors ruin manufacturing runs. A common mistake is leaving obsolete or single-sourced passive components in a design draft. By connecting an AI client to your hosted repository via MCP, you can run automated checks across your revision history. The assistant reads the parsed bill of materials, compares manufacturer part numbers across versions, and flags discrepancies long before gerbers go to the fab house.

3. Revision tracking without CAD installs

BoardRepo maintains version history for hosted hardware boards. When an assistant queries the host through MCP, it respects revision boundaries. You can ask for component changes specifically between Version 1 and Version 2 of a project. Because the underlying hardware host parses native KiCad and Altium source files into structured web models, the LLM receives accurate context tied to the exact revision line.

Ditching zip files for programmable repositories

Sending zipped design files through email or cloud folders creates dark data. Nobody indexes those zips, and nobody remembers which schematic revision had the working power stage. Hosting projects on a system that renders schematics, PCB layers, 3D models, and BOMs in the browser fixes visibility for human reviewers. Adding an MCP server integration fixes visibility for your software tools.

Connecting an AI assistant to your hardware host turns static project files into an active reference library. Stop digging through archived folders and opening CAD software just to check a component package. Expose your KiCad and Altium projects over MCP and let your assistant pull the exact hardware context you need.