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An MCP Server to utilize Codelogic's rich software dependency data in your AI programming assistant.
Configuration
View docs{
"mcpServers": {
"codelogicincengineering-codelogic-mcp-server": {
"command": "uvx",
"args": [
"codelogic-mcp-server@latest"
],
"env": {
"CODELOGIC_PASSWORD": "••••••••",
"CODELOGIC_USERNAME": "jane.doe",
"CODELOGIC_SERVER_HOST": "https://myco.app.codelogic.com",
"CODELOGIC_WORKSPACE_NAME": "default"
}
}
}
}You can integrate CodeLogic’s rich dependency data into your AI programming workflow by running the CodeLogic MCP Server locally and connecting it to your editor or IDE. This server provides tools to analyze code and database relationships, and to streamline DevOps and CI/CD integration, helping you understand the impact of changes across code, databases, and pipelines.
To leverage the CodeLogic MCP Server, configure an MCP client in your code editor or IDE to connect to the local MCP server. You can then invoke the available tools to assess how changes affect your codebase, database entities, and CI/CD pipelines. Focus on the specific methods, SQL objects, or pipeline configurations you are modifying, and examine both direct and indirect impacts before making changes.
Prerequisites you need to meet before installing the MCP server include having a compatible runtime and access to the MCP tooling described here. The recommended setup uses a local runtime to run the MCP server and connect it to your editor.
Step by step install and run flow you can follow directly in your environment is shown here for typical editor integrations. Copy the exact commands and run them in your terminal.
Configuration and usage notes for common editors are provided below. Use the instructions that match your editor to connect the MCP server, enable the desired tools, and manage environment variables for CodeLogic authentication and workspace selection.
Security considerations include keeping your CodeLogic server host, credentials, and workspace information secure. Do not share your environment variables or config files in public spaces, and restrict access to your local MCP server if you are on shared machines.
Troubleshooting tips: if the MCP server fails to launch, verify that the runtime is installed, the correct command and arguments are used for your editor, and that the environment variables are set as shown in the integration examples for your editor.
The MCP server exposes five tools across two categories for code analysis and DevOps integration. These tools help you assess impacts, generate CI/CD configurations, and share build information with the CodeLogic platform.
Use the DevOps tools to generate agent configurations for CI/CD pipelines, create build information payloads, and assemble complete pipeline configurations. These capabilities support common platforms such as Jenkins, GitHub Actions, Azure DevOps, and GitLab CI.
{
"mcpServers": {
"codelogic_mcp": {
"type": "stdio",
"command": "uvx",
"args": [
"codelogic-mcp-server@latest"
],
"env": {
"CODELOGIC_SERVER_HOST": "<url to the server e.g. https://myco.app.codelogic.com>",
"CODELOGIC_USERNAME": "<my username>",
"CODELOGIC_PASSWORD": "<my password>",
"CODELOGIC_WORKSPACE_NAME": "<my workspace>",
"CODELOGIC_DEBUG_MODE": "true"
}
}
}
}Pulls an impact assessment for a code method within its class from the CodeLogic server APIs.
Analyzes impacts between code and database entities such as tables, views, or columns.
Generates Docker agent configurations for CodeLogic scanning in CI/CD pipelines and supports multiple platforms.
Generates and sends build information to CodeLogic, including Git data, build logs, and metadata.
Creates complete CI/CD pipeline configurations for CodeLogic integration with best practices and error handling.