Recursive Control: Now Runs GPT-oss Locally via LM Studio

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We’re excited to announce a major upgrade to Recursive Control: full integration with LM Studio, now powering local execution of our GPT-oss model for recursive, agentic AI workflows.

👉 Explore the project on GitHub: flowdevs-io/Recursive-Control

What Is Recursive Control?

Recursive Control is an open-source framework designed to autonomously control your Windows computer using AI. The system can interpret natural language instructions, orchestrate workflows, and manage plugins that automate tasks like:

  • Mouse and keyboard actions
  • Command line operations
  • Browser interactions
  • File and system management

It’s powered by a multi-agent architecture (coordinator, planner, executor) and is fully extensible via plugins. Until now, most of its AI reasoning relied on cloud-based LLMs.

What’s New: Local GPT-oss via LM Studio

With LM Studio integration, Recursive Control can now run GPT-oss entirely on your machine.

Here’s what this unlocks:

  • Fully local AI — no external API calls or cloud dependencies
  • Privacy by default — your data never leaves your computer
  • No usage costs — GPT-oss is open source and free
  • Offline capability — works in disconnected environments
  • Seamless integration — Recursive Control automatically uses your local LM Studio server when enabled

🛠️ How to Get Started

  1. Clone the repo:
  2. git clone https://github.com/flowdevs-io/Recursive-Control.git
  3. Install LM Studio.
  4. Download and load GPT-oss in LM Studio.
  5. Start the LM Studio server (default endpoint: http://localhost:1234/v1).
  6. In Recursive Control’s settings, enable LM Studio and point it to your local endpoint.
  7. Run Recursive Control and issue natural language commands — GPT-oss will handle the reasoning locally.

Why This Matters

Running GPT-oss locally with Recursive Control means you get the benefits of powerful AI without the trade-offs of cloud dependency:

  • Privacy and security — nothing leaves your machine
  • No costs — no API usage fees
  • Faster responses — skip network latency
  • Offline support — works even without internet
  • Recursive orchestration — optimized for agentic control loops

🐛 Tips and Troubleshooting

  • If responses are slow, reduce max tokens or use a quantized GPT-oss build.
  • Check that LM Studio is running and accessible on http://localhost:1234/v1.
  • Enable GPU acceleration in LM Studio for faster performance.
  • Monitor system resources — larger models require more RAM and VRAM.

🚀 What’s Next

This update is just the beginning. With GPT-oss + LM Studio, Recursive Control is becoming:

  • More private — all processing is local
  • More affordable — no per-token costs
  • More resilient — runs anywhere, even offline

Next steps include adding support for additional open models, improving automatic fallback between local and cloud AI, and optimizing performance for recursive agent loops.

👉 Try it today by downloading LM Studio, setting up GPT-oss, and running Recursive Control locally: flowdevs-io/Recursive-Control

We’re excited to announce a major upgrade to Recursive Control: full integration with LM Studio, now powering local execution of our GPT-oss model for recursive, agentic AI workflows.

👉 Explore the project on GitHub: flowdevs-io/Recursive-Control

What Is Recursive Control?

Recursive Control is an open-source framework designed to autonomously control your Windows computer using AI. The system can interpret natural language instructions, orchestrate workflows, and manage plugins that automate tasks like:

  • Mouse and keyboard actions
  • Command line operations
  • Browser interactions
  • File and system management

It’s powered by a multi-agent architecture (coordinator, planner, executor) and is fully extensible via plugins. Until now, most of its AI reasoning relied on cloud-based LLMs.

What’s New: Local GPT-oss via LM Studio

With LM Studio integration, Recursive Control can now run GPT-oss entirely on your machine.

Here’s what this unlocks:

  • Fully local AI — no external API calls or cloud dependencies
  • Privacy by default — your data never leaves your computer
  • No usage costs — GPT-oss is open source and free
  • Offline capability — works in disconnected environments
  • Seamless integration — Recursive Control automatically uses your local LM Studio server when enabled

🛠️ How to Get Started

  1. Clone the repo:
  2. git clone https://github.com/flowdevs-io/Recursive-Control.git
  3. Install LM Studio.
  4. Download and load GPT-oss in LM Studio.
  5. Start the LM Studio server (default endpoint: http://localhost:1234/v1).
  6. In Recursive Control’s settings, enable LM Studio and point it to your local endpoint.
  7. Run Recursive Control and issue natural language commands — GPT-oss will handle the reasoning locally.

Why This Matters

Running GPT-oss locally with Recursive Control means you get the benefits of powerful AI without the trade-offs of cloud dependency:

  • Privacy and security — nothing leaves your machine
  • No costs — no API usage fees
  • Faster responses — skip network latency
  • Offline support — works even without internet
  • Recursive orchestration — optimized for agentic control loops

🐛 Tips and Troubleshooting

  • If responses are slow, reduce max tokens or use a quantized GPT-oss build.
  • Check that LM Studio is running and accessible on http://localhost:1234/v1.
  • Enable GPU acceleration in LM Studio for faster performance.
  • Monitor system resources — larger models require more RAM and VRAM.

🚀 What’s Next

This update is just the beginning. With GPT-oss + LM Studio, Recursive Control is becoming:

  • More private — all processing is local
  • More affordable — no per-token costs
  • More resilient — runs anywhere, even offline

Next steps include adding support for additional open models, improving automatic fallback between local and cloud AI, and optimizing performance for recursive agent loops.

👉 Try it today by downloading LM Studio, setting up GPT-oss, and running Recursive Control locally: flowdevs-io/Recursive-Control

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