Kilo Code is a powerful VS Code plugin with support for MCP (Model Context Protocol), enabling you to generate code, debug, and manage projects directly within the editor — delivering a more efficient and intelligent development experience. Kilo Code’s performance is further enhanced with the GLM Coding Plan,, helping you achieve greater efficiency and stability in both code creation and project collaboration.

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Step 1: Installing the Kilo Code Plugin

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1. Open the Extensions Marketplace

a. Launch VS Code b. Click the Extensions Marketplace icon on the left sidebar c. Search for Kilo Code in the search bar d. Locate the Kilo Code plugin Description

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2. Install the Plugin

a. Click the Install button to begin installation b. After installation, choose to trust the developer Description

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Step 2. Configuring API Settings

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1. Select API Key Authentication

Choose Use your own API key Description

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2. Enter Configuration Details

Fill in the following information as specified:
  • API Provider: Select OpenAI Compatible
  • OpenAI Base URL: Enter https://api.z.ai/api/coding/paas/v4
  • API Key: Input your Z.AI API Key
  • Model Name: Enter glm-4.5 and select Use Custom
Description

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Step 3. Configuring MCP (Optional)

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1. Add an MCP Server

Kilo Code supports MCP (Model Context Protocol) to extend the capabilities of AI models. Below is an example configuration for an SQLite MCP server: Refer to the https://github.com/modelcontextprotocol/servers-archived/tree/main/src/sqlite documentation and add the MCP configuration: 
{
    "mcpServers": {
        "SQLite": {
            "command": "uv",
            "args": [
                "--directory",
                "parent_of_servers_repo/servers/src/sqlite",
                "run",
                "mcp-server-sqlite",
                "--db-path",
                "~/test.db"
            ]
        }
    }
}

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Step 4. Getting Started

Once configured, you can enter prompts in the input box to leverage the AI model for various tasks, such as:
  • Analyzing database table structures
  • Calculating statistics and averages
  • Generating and optimizing SQL queries
  • Code generation and refactoring
  • Project analysis and documentation writing