You don't need remote APIs for a coding copliot, or the MCP Course! Set up a fully local IDE with MCP integration using Continue. In this tutorial Continue guides you through setting it up.
text
You don't need remote APIs for a coding copliot, or the MCP Course! Set up a fully local IDE with MCP integration using Continue. In this tutorial Continue guides you through setting it up.
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This is what you need to do to take control of your copilot:  
text
This is what you need to do to take control of your copilot:  
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1. Get the Continue extension from the [VS Code marketplace](
text
1. Get the Continue extension from the [VS Code marketplace](
https://marketplace.visualstudio.com/items?itemName=Continue.continue
https://marketplace.visualstudio.com/items?itemName=Continue.continue
link
) to serve as the AI coding assistant.  
text
) to serve as the AI coding assistant.  
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2. Serve the model with an OpenAI compatible server in Llama.cpp / LmStudio/ etc.
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2. Serve the model with an OpenAI compatible server in Llama.cpp / LmStudio/ etc.
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llama-server -hf unsloth/Devstral-Small-2505-GGUF:Q4_K_M
```
llama-server -hf unsloth/Devstral-Small-2505-GGUF:Q4_K_M
```
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3. Create a 
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3. Create a 
.continue/models/llama-max.yaml
`.continue/models/llama-max.yaml`
inline_code
 file in your project to tell Continue how to use the local Ollama model.
text
 file in your project to tell Continue how to use the local Ollama model.
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    name: Llama.cpp model
    version: 0.0.1
    schema: v1
    models:
      - provider: llama.cpp
        model: unsloth/Devstral-Small-2505-GGUF
        apiBase: http://localhost:8080
        defaultCompletionOptions:
          contextLength: 8192 
    # Adjust based on the model
        name: Llama.cpp Devstral-Small
        roles:
          - chat
          - edit
```
    name: Llama.cpp model
    version: 0.0.1
    schema: v1
    models:
      - provider: llama.cpp
        model: unsloth/Devstral-Small-2505-GGUF
        apiBase: http://localhost:8080
        defaultCompletionOptions:
          contextLength: 8192 
    # Adjust based on the model
        name: Llama.cpp Devstral-Small
        roles:
          - chat
          - edit
```
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4. Create a 
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4. Create a 
.continue/mcpServers/playwright-mcp.yaml
`.continue/mcpServers/playwright-mcp.yaml`
inline_code
 file to integrate a tool, like the Playwright browser automation tool, with your assistant.
text
 file to integrate a tool, like the Playwright browser automation tool, with your assistant.
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    name: Playwright mcpServer
    version: 0.0.1
    schema: v1
    mcpServers:
      - name: Browser search
        command: npx
        args:
          - "@playwright/mcp@latest"
```
    name: Playwright mcpServer
    version: 0.0.1
    schema: v1
    mcpServers:
      - name: Browser search
        command: npx
        args:
          - "@playwright/mcp@latest"
```
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Check out the full tutorial in the [the MCP course](
text
Check out the full tutorial in the [the MCP course](
https://huggingface.co/learn/mcp-course/unit2/continue-client
https://huggingface.co/learn/mcp-course/unit2/continue-client
link
)
text
)
You don't need remote APIs for a coding copliot, or the MCP Course! Set up a fully local IDE with MCP integration using Continue. In this tutorial Continue guides you through setting it up.

This is what you need to do to take control of your copilot:  

1. Get the Continue extension from the [VS Code marketplace](https://marketplace.visualstudio.com/items?itemName=Continue.continue) to serve as the AI coding assistant.  

2. Serve the model with an OpenAI compatible server in Llama.cpp / LmStudio/ etc.

```
llama-server -hf unsloth/Devstral-Small-2505-GGUF:Q4_K_M
```
3. Create a `.continue/models/llama-max.yaml` file in your project to tell Continue how to use the local Ollama model.
```
    name: Llama.cpp model
    version: 0.0.1
    schema: v1
    models:
      - provider: llama.cpp
        model: unsloth/Devstral-Small-2505-GGUF
        apiBase: http://localhost:8080
        defaultCompletionOptions:
          contextLength: 8192 
    # Adjust based on the model
        name: Llama.cpp Devstral-Small
        roles:
          - chat
          - edit
```

4. Create a `.continue/mcpServers/playwright-mcp.yaml` file to integrate a tool, like the Playwright browser automation tool, with your assistant.

```
    name: Playwright mcpServer
    version: 0.0.1
    schema: v1
    mcpServers:
      - name: Browser search
        command: npx
        args:
          - "@playwright/mcp@latest"
```

Check out the full tutorial in the [the MCP course](https://huggingface.co/learn/mcp-course/unit2/continue-client)
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