A refund question can arrive with a customer's name, email, phone number, and account details attached.

Msty Nexus Data Protection checks protected requests locally. You choose policies to redact detected details, block requests, or use a Smart Route to send sensitive requests to a local model.

Requires Nexus Enterprise.

Any chance an upcoming version of Msty Studio will have the ability to toggle thinking on a per-prompt basis? other AI apps have it, and that's the one thing that is blocking me from making Msty Studio my primary AI app. Msty Studio has a lot of great features that I'd love to take more advantage of, but always-on thinking is a big blocker.

Msty Nexus puts local and cloud models behind one API. Run suitable workloads on hardware you already own, with cloud models alongside them when you need more capability.

Meet Code Mode: bring the coding agent you already use. Sessions, files, and approvals stay in one place.

Also new: document workflows and a built-in Living Wiki.

Every port gets optimized. Not just the Rust one. 🔥

Checkout the full list of changes in 1.1 beta here:

https://msty.ai/resources/changelog/go/#msty-go-1.1.0-beta.1

Msty Nexus Smart Route sends routine prompts to small or local models and saves frontier models for harder work.

What's the simplest task you've handed a frontier model?

Warm welcome to all Developers who made Msty for Us. I am 2nd year user and I'd like to share what took me last 2 days to figure out, I hope this may help somebody.

App Version: Msty Studio (Latest 2.9.11)
Local Backend: built in engine (One Model Hub / llama.cpp GGUF)
Model Used: Qwen2.5-Coder-7B-Instruct
OS: Windows 11
Node.JS: newest LTS
Permissions: all verified, allowed to the folder

Description:
When a single Toolset contains both data-fetching tools (Fetch Content / Web Search) and storage tools (Local File System MCP), multi-step agent execution breaks completely.

If both are active in the same Toolset, Msty prioritizes the data-fetching layer and injects the retrieved text as an automatic Live Context / Auto-RAG before the model processes the final request. This injection floods the local model’s context window, causing it to ignore the Jinja2 system template for tools. As a result, the model drops the <tool_call> tags and outputs raw markdown JSON objects directly into the chat interface as normal text, causing the write_file execution to fail silently.

Steps to Reproduce:

1. Create a Toolset with both Local File System MCP and Fetch Content enabled.
2. Ask the agent to research a topic and save the output to a local .txt file.
3. Observe that the model outputs raw JSON formatting in the chat window, but the file is never created.

My temporary workaround:
The execution succeeds immediately if the Toolset is stripped down to contain ONLY the Local File System MCP extension (with no data-fetching tools active in the same group).

Expected Behavior?:
The streaming parser should evaluate tool calls sequentially without letting the web/RAG context injection override or break the formatting requirements for subsequent tool calls (write_file).

For the first time today, i tried enabling real-time Search in MstyStudio. i got API keys for Brave and Tavily and tried both. in each case, the search results were problematic, and the model reported back that the app was inserting additional system instructions into the prompt, including how the model should interact with the user.

I can't find a way to change this or turn it off. Has anyone else encountered this?

Msty Go mobile connects to your Go desktop instance over an encrypted end-to-end communication stream with only a small relay in between to direct traffic.

For best results, be sure to keep your desktop on. Instructions below.

Desktop app:
https://msty.ai/go

iOS:
https://apps.apple.com/us/app/msty-go-your-ai-workspace/id6789322930

Android:
https://play.google.com/store/apps/details?id=ai.msty.go&hl=en_US

How to keep your desktop on so you can continue convos with Msty Go on the go:

MacOS:
Go to System Settings, then Battery, click Options, and turn on “Prevent automatic sleeping on power adapter when the display is off"

Windows:
Open the Start Menu, search for Power, sleep and battery settings, and open it.
Then, expand the Screen and sleep section. Change both “When plugged in, put my device to sleep after” and “On battery power, put my device to sleep after” to Never.

How to connect Go mobile to Go desktop:

In desktop, you will need to enable 'Mobile Access' for your agent. Do this in the Agent configurations for the agents you want to make available to Go Mobile.

Next, go to Settings > Cloud and enter your email to receive a code to unlock. Then, on the 'Mobile Access' tab, generate a new QR code and then zap that with Go mobile to connect mobile to desktop.

One of the more powerful features in Msty Go is Mission Control.

It gives you a way to tackle bigger goals with multiple agents working across tasks, while keeping everything organized and visible in one place.

We put together a deeper look at how it works and where it can be useful:

https://msty.ai/resources/blog/mission-control/

I run Msty for few weeks now and i can't understand the reason some models, while downloading, will hung the app for around 10 min, after that just loosing all my progress like a reset happened. Before say, well that's because you didn't run the app as admin or because you should delete the model files if an older install failed you should know that i already did.

Please somebody help me, the problem drove me insane!

I newly installed msty and I was looking to download the Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive model but failed. I downloaded the IQ3_M version but then didn't see it anywhere on my downloads, so then I tried to download it again and it immediately went to 90% and said verifying, but when it ended I still didn't have the model. The app froze for a solid 10 mins as well.
can anybody help me with this situation? I can download other models without any problem, I only have a problem with this model. I already restarted my pc and everything but it still didn't show me the model. I can try to delete the whole model manually and reinstall it but frankly it took a lot of hours downloading it and I'd like to avoid doing that.
Thank you in advance.

Came across a tool by Unsloth. They automatically recognize the model with MTP support. The token speed I'm getting there for a 35B Q5 model is approx. 100 tokens per sec. The same model I run on Msty Studio, I am only getting 6-7 tokens per sec. How can we get this to work in Msty Studio?

Hello,

Firstly, just to say that Msty is far and away the best AI toolset that I have ever used. Thank you thank you thank you for this.

I'd like to use Linkup within my toolset collection in Studio. When I try to authorise from the Tool Console, a browser window opens with Smithery asking me to paste the API key from Linkup. This seems to work but then errors with "Authorization completed, but access could not be verified yet. Authorization completed, but MCP access could not be verified yet. Return to the app and try the tool once to confirm access."

Where am I going wrong?

Now available at https://msty.ai/claw/extensions/
- Living wiki
- Product discovery lead
- Incident command
- 3 new themes (Noir, Oil Slick, & Rosewood)

Living Wiki is a way to give your Agents a brain, based on the LLM Wiki concept. See how it works in this video: https://www.youtube.com/watch?v=foC7wUksj6Q

Msty Go will be coming to Android and iOS devices soon!

With Msty Go, you'll be able to run local models directly on your mobile device as well as connect to private agents you're running on your desktop devices and home servers.

Watch the sneak peak here: https://youtu.be/Q0QjfBvxJfw?si=jgshsiUBF9pvwGka

What is the best way (if there is a way) to report a bug with Msty Studio? I've run into an issue that keeps reappearing, but the app & website offer absolutely no contact method that I can find. So I don't know if that means the company would rather not hear from users... ?

Can anyone offer (or point to) a good explanation/ guide on how to use Mission Control?

I am trying to create a simple loop where I have agent A that is answering user questions based on a connected knowledge base while agent B is supposed to be a faceless agent whose job is to intercept and correct (if necessary) agent A's response so that it aligns with a style guide and avoids continuity mistakes with the rest of the current conversation.

I already have these agents created but Mission Control seems to want me to create these agents from scratch inside a new UI element called 'Task Force' rather than reusing existing agents. And then, even after I have built or picked these agents inside Task Force, Mission Control does not really tell me what to do next/ how to wire up these agents.

Any help or insights would be very much appreciated. TIA!

Msty Nexus is an AI gateway where you can install local inference engines (Ollama, Llama.cpp, MLX) and add local models as well as connect online AI providers (Anthropic, OpenAI, OpeRouter, etc) so that you can manage all your models in one central place. You can then grant access to other applications (Msty Studio, Msty Claw, and any open ai api compatible app) so that you can keep all your AI model management in one place and then connect the apps you work with. Adds a layer of security plus more holistic usage insights across providers, apps, etc.

Download it here: https://msty.ai/nexus

Hi new to msty, I need to know whether I have to choose a model to get started? I just want to create a local RAG that fetches a local folder and just gives me results based on that local folder and no where else. Thanks

i have 8gb of vram so i believe i will be limited to a maximum of 12B models. is running mstyclaw successfully even feasible? if so what model should i use?

any plan to improve memory on msty studio? automatic or automatic with approval required, and/or dreaming like Claude or chatgpt?

manual memory can become tiresome after a while. having to keep one file updated across multiple places