MCP.Market

Chiplab MCP server

online · 100% uptime
by veecle.ai·ai.veecle/chiplab·v1.0.0·16 stars

Run, build, and validate firmware on virtual hardware from your AI agent. Hardware knowledge corpus.

A100/100grade A
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Safety scan
A100/100

full report

Adoption
Growing

16 stars

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If you have run it, two minutes of your experience saves the next person an afternoon.

Chiplab tools

Tool list not cached yet. `describe` through the gateway fetches it live.

Public scan report

scanner v0.1.9 · 2026-09-26 · same rubric, same numbers if you re-run it

no findings
  • –Code scanremote-only server, no package to scann/a
  • Live reliabilityremote reachable in 618ms (auth required)20/20
  • –Tool poisoningtools not inspected (endpoint requires auth); not countedn/a
  • Auth qualityOAuth resource metadata advertised on 40115/15
  • Maintenancelast push 11 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year; website matches verified namespace10/10
Overall 100/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Chiplab compares

Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
100/100
higher than 100% of 4,460 AI and agents servers
Uptime
100%
of our recent checks; the typical remote AI and agents server answers 100%
Response time
982 ms
faster than 9% of 2,331 AI and agents servers
GitHub stars
16
more than 87% of 2,711 AI and agents servers

Install Chiplab in Claude Code, Cursor or VS Code

claude mcp add --transport http chiplab https://chiplab.veecle.ai/mcp
Add to Cursor

What the publisher says

From the Chiplab repository's README, as published. We do not edit it. Read it on GitHub

Chiplab

Simulate & validate firmware on virtual instances of real chips, straight from your AI coding agent — no hardware.

Chiplab is a hosted MCP service. Your AI coding agent connects to it, uploads compiled firmware, runs it on a virtual instance of a real microcontroller, and reads back the UART output. You don't drive the toolchain — your agent does.

We're building the next way to develop chips, in the open and early. Today it runs Hello world! on STM32 and Nordic boards; a lot more is on the way — see veecle.ai. Try it, poke at it, and tell us what you'd like to see.

Quickstart

  1. Create a free account at veecle.ai (no credit card).
  2. Connect your agent to the Chiplab MCP server.
  3. git clone https://github.com/veecle/chiplab && cd chiplab, then tell your agent:

"Set up Chiplab and run the stm32f4-discovery example on it."

Your agent reads AGENTS.md, installs what it needs, builds the firmware, uploads it, runs it on the virtual board, and reports Hello world! back from the chip's UART. That's the whole loop.

Connect your agent

Chiplab is an HTTP MCP server at https://chiplab.veecle.ai/mcp. Most clients take the standard mcpServers schema:

{
  "mcpServers": {
    "chiplab": {
      "type": "http",
      "url": "https://chiplab.veecle.ai/mcp"
    }
  }
}

On first use your client opens a browser to sign in. To verify, ask your agent to call Chiplab's discovery/help tool with no arguments.

Claude Code

If you cloned this repo, the server is already configured via .mcp.json — Claude Code will prompt you to trust it. Otherwise:

claude mcp add --transport http chiplab https://chiplab.veecle.ai/mcp

Claude Desktop / Cursor

Use the mcpServers block above in claudedesktopconfig.json or .cursor/mcp.json.

VS Code

Same block in .vscode/mcp.json, but under a servers key instead of mcpServers.

Codex

TOML in ~/.codex/config.toml:

[mcp_servers.chiplab]
url = "https://chiplab.veecle.ai/mcp"

Then sign in with codex mcp login chiplab.

How it works

The contract is framework-agnostic: your agent builds an ELF → uploads it → runs it on the target board → reads the captured UART output. Runs return synchronously and are bounded to a fixed amount of virtual time.

This repo ships a ready-to-run example for every supported board, grouped by framework — bare-metal (Rust, vendor HAL), embassy-rust ([Embassy] async), zephyr-os ([Zephyr RTOS], C), freertos ([FreeRTOS], C), and threadx ([Eclipse ThreadX], C). The full board × framework matrix is in supported-boards.md.

[Embassy]: https://embassy.dev [Zephyr RTOS]: https://zephyrproject.org [FreeRTOS]: https://www.freertos.org [Eclipse ThreadX]: https://github.com/eclipse-threadx/threadx

Toolchain and build details live in each framework's directory (examples//README.md for humans, AGENTS.md for agents) — your agent finds them on its own. Prefer building by hand? Each framework README has the exact commands.

To run your own firmware, build an ELF for a supported board and ask your agent to upload and run it the same way.

Contributing

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Chiplab: common questions

Is Chiplab MCP server safe?
Yes, by our scan: it is graded A (100/100). Read the Chiplab safety report
How do I install Chiplab?
It runs remotely at chiplab.veecle.ai. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.
Does Chiplab need an API key?
No key to paste: it signs you in with OAuth when your client connects.
Is Chiplab maintained?
The last commit was 50 days ago (2026-09-15). The latest release is v1.0.0.
Is Chiplab up?
100% of our last 28 checks got an answer. We check remote servers about four times a day.
What can I use instead of Chiplab?
Servers from other publishers that do the same job: Basic Memory MCP server, IWE (iwe.md) MCP server and Total Agent Memory MCP server.
How does Chiplab compare with other AI and agents MCP servers?
safety score 100/100 (higher than 100% of 4,460 AI and agents servers); uptime 100% (of our recent checks; the typical remote AI and agents server answers 100%); response time 982 ms (faster than 9% of 2,331 AI and agents servers). Full comparison.

Alternatives to Chiplab

Same job from other publishers: the closest match first, then the best rated.

  • Basic Memory
    Local-first knowledge management with bi-directional LLM sync via Markdown files.
    B
  • IWE (iwe.md)
    Markdown knowledge base as agent memory. Runs against the notes directory it is started in.
    A
  • Total Agent Memory
    Persistent local memory for coding agents: temporal knowledge graph, procedural and episodic recall
    A