Kaimon.jl

Kaimon.jl is an MCP server that exposes a live Julia session to connected AI agents. It enables agents like Claude Code, Cursor, or other MCP clients to execute Julia code, inspect runtime state, introspect types and methods, run tests, and perform semantic code search by leveraging Julia's runtime and Kaimon’s Gate integration. The server presents a rich set of tools categorized into code execution, introspection, code analysis, navigation, debugging, packaging, testing, and semantic search, all accessible through MCP commands generated from Julia function signatures and gate snippets. To begin, deploy the container and connect via your MCP client using the server’s endpoint; once connected, you’ll see a session that the agent can call into with provided tool names (for example, ex for executing code, investigate_environment for introspection, goto_definition for navigation, and qdrant_search_code for semantic search depending on your configuration).

From the MCP client, you can write config snippets to register specific tools or Gate integrations. Kaimon auto-generates MCP schemas from Julia function signatures when you expose a GateTool with serve, enabling the agent to call domain-specific logic exactly as if it were a built-in tool. The dashboard and keyboard shortcuts within the Kaimon UI give quick access to write configs, auto-connect Gate snippets, and manage sessions across multiple REPLs. The server also supports security modes and API key management, making it suitable for both exploratory sessions and production-grade agent interactions.

Prerequisites:

• Docker installed and running
• Basic knowledge of MCP clients (e.g., Claude Code, Cursor) and how to connect to an MCP server

Installation steps:

1. Pull the Kaimon.jl Docker image (or build your own if you have a local build): docker pull kaimon/kaimon.jl:latest

2. Run the container exposing the MCP port (adjust port as needed): docker run -p 8080:8080 -i kaimon/kaimon.jl:latest

3. Verify the container starts correctly and the MCP endpoint is reachable. If your image exposes a startup script, you may see a setup wizard for security mode, API key, and port configuration.

4. Configure your MCP client to connect to the endpoint shown by the container (default port 8080 unless overridden).

5. (Optional) If you prefer local development, clone the repo and run Julia locally, ensuring you follow any project-specific setup steps documented in the repository.

Notes and tips:

• The Kaimon.jl server exposes a Gate mechanism to connect Julia processes and register domain-specific tools. You can expose functions in GateTool and have the MCP client call them directly, with automatic schema generation based on function signatures.
• If you enable semantic code search, consider setting up Qdrant as described in the project’s documentation for indexing and querying code across your workspace.
• Security is configurable (strict/relaxed/lax); configure API keys and IP allowlists to restrict access.
• When troubleshooting, check logs for tool registration and session creation messages to ensure tools are exposed correctly to the MCP client.
• If you need to scale, you may run multiple containers and load balance MCP connections across them; ensure that session state is managed according to your use case.