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MCP

Automate GNURadio Flowgraph Creation

MCP server for Claude Code that works with GNU Radio to build and simulate RF receivers, producing SigMF captures and flowgraphs.

Connect
Works with githubpython
Julius
Maintainer?
17
Spark score
out of 100
Updated 10 days ago
Version V1
Models
claude
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Why it matters

Programmatically create, modify, and save GNURadio flowgraphs (.grc files) using an MCP server. This asset is designed for AI-driven automation and integration with LLMs.

Outcomes

What it gets done

01

Generate GNURadio flowgraphs from code or automation scripts.

02

Edit and save existing .grc files programmatically.

03

Integrate with AI and automation tools for dynamic flowgraph management.

04

Facilitate automated testing and debugging of GNURadio applications.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-gnuradio | bash

Overview

Gnuradio MCP Server

What it does

GNU Radio MCP server for RF receiver workflows

How it connects

when prototyping RF receivers or analyzing spectrum captures in Claude Code

Source README

Marconi 🤖

        o)))
        |
    .-------.
    | o   o |
    |   v   |
    '-------'

    Hi! I'm Marco.

LLM-driven RF for Claude Code. Describe what you want on the air and I survey the
spectrum, build and run the receiver, look at the signal, and leave a reproducible
RF project behind - SigMF captures, YAML pipelines, and .grc flowgraphs you own.

Early development - v1.0 is simulation-only (no hardware yet). See ROADMAP.md.

Proviously known as GNURadio/GR-MCP.

Requirements

  • uv and Python ≥ 3.13
  • GNU Radio 3.10+ installed system-wide (conda-forge,
    your distro's package manager, or Homebrew) - needed to run pipelines and
    simulate. Analyzing existing IQ files doesn't require it.

Install

In Claude Code:

/plugin marketplace add yoelbassin/gr-mcp
/plugin install marconi

That's it - uv starts the MCP server on first use and loads the skills. Nothing
else to configure.

Use it

Ask in plain language:

"Simulate an FM station at 100.3 MHz and build me a receiver."

"Here's a capture, mystery.wav - survey what's on the air, then decode the strongest carrier."

I pick the right skill and drive the workflow end to end:

  • survey-spectrum - what's present (PSD, signal detection, spectrogram)
  • simulate-scene - register a simulated device from a description
  • build-receiver - channelize, demodulate, validate, run, verify, save
  • debug-no-signal - locate the fault when a receiver outputs nothing
  • tx-experiment - closed-loop transmit-then-receive in simulation
  • escape-hatch - drop to the Python library when no tool fits

Artifacts land under artifacts/ in the server's working directory; set
MARCONI_WORKSPACE to put them elsewhere.

Discussion

Questions & comments · 0

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