Question 1

What is CodeAlive MCP Server?

Accepted Answer

CodeAlive MCP (Model Context Protocol) Server is a tool that enables AI clients (like Claude, Copilot, Cursor) to access CodeAlive's semantic code search and codebase interaction features, providing enriched context from your project's codebase.

Question 2

How does CodeAlive MCP Server enhance AI agents?

Accepted Answer

It enhances AI agents by enabling them to find relevant code faster, understand the bigger picture of the codebase, and reduce costs and time by providing accurate context directly.

Question 3

What AI clients are compatible with CodeAlive MCP Server?

Accepted Answer

CodeAlive MCP Server is compatible with AI clients like Claude Desktop, Cursor, Windserf, VS Code (GitHub Copilot), Cline, Roo-Code, and Refact.

Question 4

What are the prerequisites for using CodeAlive MCP Server?

Accepted Answer

The prerequisites include Python 3.11, uv (recommended) or pip, and a CodeAlive account with an API Key.

Question 5

How do I get an API key for CodeAlive?

Accepted Answer

You can obtain an API key by logging into your CodeAlive account at https://app.codealive.dev/, navigating to the API Keys section, and creating a new API key with the appropriate scope.

Question 6

How do I install CodeAlive MCP Server?

Accepted Answer

You can install it by cloning the repository from GitHub and using uv or pip to install the dependencies within a virtual environment.

Question 7

What environment variables are supported by CodeAlive MCP Server?

Accepted Answer

The supported environment variable is CODEALIVE_API_KEY, which is your CodeAlive API key.

Question 8

How do I integrate CodeAlive MCP Server with Continue?

Accepted Answer

You can integrate it by configuring the MCP server in your project's .continue/config.yaml or globally in ~/.continue/config.yaml with the appropriate command, arguments, and environment variables.

Question 9

How do I integrate CodeAlive MCP Server with Claude Desktop?

Accepted Answer

You can integrate it by editing your Claude Desktop configuration file (claude_desktop_config.json) and adding the MCP server configuration with the correct command, arguments, and environment variables.

Question 10

How do I integrate CodeAlive MCP Server with Visual Studio Code with GitHub Copilot?

Accepted Answer

You can integrate it by adding the MCP server configuration to your settings.json file in VS Code, ensuring the correct command, arguments, and environment variables are set.

Question 11

How do I integrate CodeAlive MCP Server with Cursor?

Accepted Answer

You can integrate it by opening Cursor settings, navigating to the MCP section, adding a new global MCP server, and entering the JSON configuration with the appropriate paths and API key.

Question 12

What do I do if the MCP server isn't working correctly?

Accepted Answer

You can enable debug logging, check the MCP server output, check client logs, verify configuration, and ensure your API key is correct. You can also contact support@codealive.dev for assistance.

Question 13

What is UBOS and how does it relate to CodeAlive MCP Server?

Accepted Answer

UBOS is a full-stack AI Agent Development Platform focused on bringing AI Agents to every business department. Integrating CodeAlive MCP Server with UBOS can enhance AI agent performance by providing a central platform for managing AI agents, seamless data integration, customizable AI Agents, and multi-agent systems.

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