diff --git a/4_integrations/claude-code.md b/4_integrations/claude-code.md
index 4c63252..5202970 100644
--- a/4_integrations/claude-code.md
+++ b/4_integrations/claude-code.md
@@ -1,7 +1,7 @@
 ---
 title: Claude Code
 description: Use Claude Code with LM Studio
-index: 2 
+index: 2
 ---
 
 Claude Code can talk to LM Studio via the Anthropic-compatible `POST /v1/messages` endpoint.
diff --git a/4_integrations/index.md b/4_integrations/index.md
index 8502bd8..1176710 100644
--- a/4_integrations/index.md
+++ b/4_integrations/index.md
@@ -15,3 +15,4 @@ We provide guides below for popular tools and are constantly expanding this list
 
 - [Claude Code](/docs/integrations/claude-code)
 - [Codex](/docs/integrations/codex)
+- [Onyx](/docs/integrations/onyx)
diff --git a/4_integrations/onyx.md b/4_integrations/onyx.md
new file mode 100644
index 0000000..df7ec6b
--- /dev/null
+++ b/4_integrations/onyx.md
@@ -0,0 +1,70 @@
+---
+title: Onyx
+description: Use Onyx with LM Studio
+index: 4
+---
+
+[Onyx](https://www.onyx.app/) is an open source AI platform that connects your LLMs to your organization's knowledge and applications. It provides chat, AI agents, internal search, web search, actions, and more — all in one place.
+
+Onyx has a built-in integration to LM Studio that auto-discovers your loaded models, so setup takes just a few clicks.
+
+
+
+```lms_protip
+Have a powerful LLM rig? Use [LM Link](/docs/integrations/lmlink) to run Onyx from one machine while the model runs on another.
+```
+
+## Quick Start: Self-Hosted Onyx
+
+For full data privacy, you can self-host both Onyx and LM Studio on your own infrastructure.
+
+### 1) Deploy Onyx
+
+Run the Onyx install script (requires Bash, Docker, and at least 4 CPU cores / 8GB RAM):
+
+```bash
+curl -fsSL https://raw.githubusercontent.com/onyx-dot-app/onyx/main/deployment/docker_compose/install.sh > install.sh && chmod +x install.sh && ./install.sh
+```
+
+The script will pull containers and start Onyx. Once running, access the Onyx UI at `http://localhost:3000`.
+
+For more deployment options (Kubernetes, cloud providers, etc.), see the [Onyx deployment docs](https://docs.onyx.app/deployment/getting_started/quickstart).
+
+### 2) Start LM Studio's local server
+
+```bash
+lms server start --port 1234
+```
+
+If LM Studio is running on a different machine than Onyx, make sure the LM Studio server is accessible from the Onyx host (e.g., `http://<lm-studio-host>:1234`).
+
+### 3) Add LM Studio as a provider in Onyx
+
+Navigate to **Admin Panel → Configuration → LLM** and select **LM Studio** from the list of providers.
+
+Set the **API Base URL** to your LM Studio server address:
+
+
+| Field            | Value                                                                                     |
+| ---------------- | ----------------------------------------------------------------------------------------- |
+| **API Base URL** | `http://localhost:1234` (or `http://<lm-studio-host>:1234` if on a different machine)     |
+| **API Key**      | Leave blank unless you have [authentication](/docs/developer/core/authentication) enabled |
+
+
+Onyx will automatically connect and discover your loaded models, including their context length and capabilities (vision, reasoning).
+
+
+
+### 4) Select your model and start chatting
+
+Enable your models from the auto-discovered list, save, and you're ready to go!
+
+---
+
+## Tips
+
+- Onyx auto-discovers models loaded in LM Studio along with their capabilities (vision, reasoning) and context length.
+- For best results, use a model with strong instruction-following and tool-use capabilities (e.g., Qwen 3.5).
+- Check out the [Onyx docs](https://docs.onyx.app/) for more details on setup and configuration.
+
+If you're running into trouble, hop onto the [LM Studio Discord](https://discord.gg/lmstudio) or the [Onyx Discord](https://discord.gg/Pk3qzRKAEx)!