runpod · mintlify · Aug 17, 2026 · Aug 17, 2026
diff --git a/get-started/mcp-servers.mdx b/get-started/mcp-servers.mdx
@@ -1,37 +1,37 @@
 ---
 title: "Use Runpod's MCP servers"
 sidebarTitle: "MCP servers"
 description: "Connect AI tools to Runpod using the Model Context Protocol for infrastructure management and documentation access."
 tag: "NEW"
 ---

 Runpod provides two [Model Context Protocol (MCP)](https://modelcontextprotocol.io/docs/getting-started/intro) servers that connect AI tools and coding agents directly to Runpod:

 - **[Runpod API MCP server](#runpod-api-mcp-server):** Manage Pods, endpoints, templates, volumes, and registries through the Runpod REST API. Requires a [Runpod API key](/get-started/api-keys).
 - **[Runpod docs MCP server](#runpod-docs-mcp-server):** Search Runpod documentation for features, code examples, and guides. No authentication required.

 ## Runpod API MCP server

 The Runpod API MCP server gives AI tools access to the [Runpod REST API](/api-reference/overview), letting you create and manage Pods, Serverless endpoints, templates, network volumes, and container registries through natural language.

 **Endpoint:** Available via npm package `@runpod/mcp-server`

 **Source code:** [github.com/runpod/runpod-mcp](https://github.com/runpod/runpod-mcp)

 **Authentication:** Requires a [Runpod API key](/get-started/api-keys)

 ### Supported clients

 - [Claude Code](#claude-code)
 - [Codex CLI](#codex-cli)
 - [Cursor](#cursor)
 - [VS Code with Copilot](#vs-code-with-copilot)
 - [Claude Desktop](#claude-desktop)
 - [Windsurf](#windsurf)
 - [Cline](#cline)
 - [Gemini CLI](#gemini-cli)

 ### Claude Code

 ```bash
 claude mcp add runpod --scope user -e RUNPOD_API_KEY=your_api_key_here -- npx -y @runpod/mcp-server@latest
@@ -39,9 +39,9 @@

 Replace `your_api_key_here` with your Runpod API key. The `--scope user` flag makes the server available across all your projects. Run `/mcp` inside Claude Code to verify the connection.

 ### Codex CLI

 [Codex CLI](https://github.com/openai/codex) is OpenAI's terminal-based coding agent.

 ```bash
 codex mcp add runpod --env RUNPOD_API_KEY=your_api_key_here -- npx -y @runpod/mcp-server@latest
@@ -49,7 +49,7 @@

 ### Cursor

 Add the following to `.cursor/mcp.json` (project-level) or `~/.cursor/mcp.json` (global). This configuration works with both the Cursor IDE and the [Cursor Agent](https://cursor.com/docs/cli/mcp):

 ```json
 {
@@ -65,9 +65,9 @@
 }
 ```

 ### VS Code with Copilot

 1. Open the Command Palette (Ctrl+Shift+P on Windows/Linux or Cmd+Shift+P on macOS).
 2. Run **MCP: Add Server** and select **stdio**.
 3. Enter the following details:
   - **Name:** `Runpod`
@@ -76,7 +76,7 @@
 4. Add environment variable `RUNPOD_API_KEY` with your Runpod API key.
 5. Select **Global** or **Workspace** and click **Add**.

 ### Claude Desktop

 Add the following to your Claude Desktop config file:

@@ -101,7 +101,7 @@

 ### Windsurf

 Edit `~/.codeium/windsurf/mcp_config.json` (or open from **Settings** > **Cascade** > **MCP Servers** > **View raw config**):

 ```json
 {
@@ -136,9 +136,9 @@
 }
 ```

 ### Gemini CLI

 Add to `~/.gemini/settings.json` (global) or `.gemini/settings.json` (project-level):

 ```json
 {
@@ -179,6 +179,20 @@
 - Cloud Type: SECURE
 ```
 
+To attach an existing [network volume](/storage/network-volumes) at Pod creation, include its ID and mount path. The MCP server forwards these to the REST API's `networkVolumeId` and `volumeMountPath` fields on [`POST /pods`](/api-reference/pods/POST/pods):
+
+```
+Create a new Runpod Pod with the following specifications:
+- Name: ml-training-pod
+- Image: runpod/pytorch:2.1.0-py3.10-cuda11.8.0-devel-ubuntu22.04
+- GPU Type: NVIDIA GeForce RTX 4090
+- GPU Count: 1
+- Network Volume ID: vol_abc123
+- Volume Mount Path: /workspace
+```
+
+The network volume's data center constrains where the Pod can run, so pick a GPU type that is available in the volume's region.
+
 ```
 Create a Runpod Serverless endpoint with the following configuration:
 - Name: image-generation-endpoint
@@ -191,21 +205,21 @@
 Stop the Pod named "ml-training-pod"
 ```

 ## Runpod docs MCP server

 The Runpod docs MCP server provides access to Runpod's documentation knowledge base, making it easier to get answers about features and how to use them.

 **Endpoint:** `https://docs.runpod.io/mcp`

 **Authentication:** None required

 ### Claude Code

 ```bash
 claude mcp add runpod-docs --scope user --transport http https://docs.runpod.io/mcp
 ```

 ### Codex CLI

 ```bash
 codex mcp add runpod-docs --url https://docs.runpod.io/mcp
@@ -225,14 +239,14 @@
 }
 ```

 ### VS Code with Copilot

 1. Open the Command Palette (Ctrl+Shift+P on Windows/Linux or Cmd+Shift+P on macOS).
 2. Run **MCP: Add Server** and select **HTTP**.
 3. Enter `https://docs.runpod.io/mcp` as the URL and `Runpod Docs` as the name.
 4. Select **Global** or **Workspace** and click **Add**.

 ### Claude Desktop

 1. Open **Settings** in Claude Desktop.
 2. Navigate to **Connectors** and select **Add custom connector**.
@@ -267,9 +281,9 @@
 }
 ```

 ### Gemini CLI

 Add to `~/.gemini/settings.json`. Note that Gemini CLI uses `httpUrl` instead of `url`:

 ```json
 {
@@ -283,7 +297,7 @@

 ### Other clients

 For any other MCP-compatible client, use URL `https://docs.runpod.io/mcp` (HTTP transport).

 ### Usage examples


diff --git a/pods/manage-pods.mdx b/pods/manage-pods.mdx
@@ -1,11 +1,11 @@
 ---
 title: "Manage Pods"
 description: "Create, start, stop, and terminate Pods using the Runpod console or CLI. Review setup, configuration, and operations guidance for Runpod Pods."
 ---

 import { MachineTooltip, TemplatesTooltip } from "/snippets/tooltips.jsx";

 This page covers the core Pod management operations. For CLI usage, first [install the Runpod CLI](/runpodctl/overview) and configure your API key:

 ```sh
 runpodctl config --apiKey RUNPOD_API_KEY
@@ -13,16 +13,16 @@

 ## Quick reference

 | Action | Web UI | CLI |
 |--------|-----|-----|
 | **Deploy** | [Pods page](https://www.console.runpod.io/pods) → Deploy | `runpodctl pod create --name NAME --gpu-id "GPU" --image "IMAGE"` |
 | **Start** | Expand Pod → Play icon | `runpodctl pod start POD_ID` |
 | **Stop** | Expand Pod → Stop icon | `runpodctl pod stop POD_ID` |
 | **Update** | Three-dot menu → Edit Pod | `runpodctl pod update POD_ID` |
 | **Terminate** | Expand Pod → Trash icon | `runpodctl pod delete POD_ID` |
 | **List** | [Pods page](https://www.console.runpod.io/pods) | `runpodctl pod list` |

 ## Deploy a Pod

 <Tip>
 Deploy preconfigured Pods from the [Runpod Hub](/hub/overview#deploy-as-a-pod) for quick setup.
@@ -95,9 +95,9 @@
 </Tab>
 </Tabs>

 ## Stop a Pod

 Stopping a Pod releases the GPU and preserves data in `/workspace` (volume disk). Container disk data is cleared.

 <Warning>
 You'll still be charged for [volume disk storage](/pods/storage/types#volume-disk) while stopped. Terminate the Pod if you don't need to retain your environment.
@@ -107,6 +107,10 @@
 When using a [network volume](/storage/network-volumes), your `/workspace` data is preserved whether you stop or terminate the Pod.
 </Tip>
 
+<Warning>
+Linux commands like `shutdown`, `poweroff`, and `halt` do not stop a Pod. Pods run as containers, not VMs, so these commands only affect the container's init process. The container may restart instead of stopping. To stop a Pod from inside itself, use `runpodctl pod stop $RUNPOD_POD_ID` from the CLI tab below, or call the REST API.
+</Warning>
+
 <Tabs>
 <Tab title="Web">
 
@@ -139,9 +143,9 @@
 </Tab>
 </Tabs>

 ## Start a Pod

 Resume a stopped Pod. Note: You may be allocated [zero GPUs](/pods/troubleshooting/zero-gpus) if capacity has changed.

 <Tabs>
 <Tab title="Web">
@@ -170,7 +174,7 @@
 </Tab>
 </Tabs>

 ## Update a Pod

 Modify an existing Pod's configuration, such as storage size, image, ports, or environment variables.

@@ -207,7 +211,7 @@
 </Tabs>


 ## Terminate a Pod

 <Danger>
 Terminating permanently deletes all data not stored in a [network volume](/storage/network-volumes). Export important data first.
@@ -244,8 +248,8 @@

 Pods provide two log types:

 - **Container logs**: Application output (stdout)
 - **System logs**: Pod lifecycle events (startup, shutdown, errors)

 Access logs from the [Pods page](https://www.console.runpod.io/pods) by expanding your Pod and clicking **Logs**.

@@ -254,7 +258,7 @@
 | Issue | Solution |
 |-------|----------|
 | **Zero GPUs on restart** | See [Zero GPU Pods](/pods/troubleshooting/zero-gpus) |
 | **Pod stuck initializing** | Check logs for command errors; ensure you have an idle job (e.g., `sleep infinity`) if using SSH |
 | **Docker Compose not working** | Not supported. Use a [custom template](/pods/templates/overview) with your dependencies baked in. |

 Need help? [Contact support](https://www.runpod.io/contact).