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MCP server · Files

Julia MCP

MCP server for persistent Julia sessions — fast iteration without startup/compilation overhead

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Scored 6 months ago · breakdown

About Julia MCP

Julia MCP is an MCP server in the Files category: mCP server for persistent Julia sessions — fast iteration without startup/compilation overhead.

Install

From source
git clone https://github.com/aplavin/julia-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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  • ✓README presentThe repository ships documentation.

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README

julia-mcp

MCP server that gives AI assistants access to efficient Julia code execution. Avoids Julia's startup and compilation costs by keeping sessions alive across calls, and persists state (variables, functions, loaded packages) between them — so each iteration is fast.

  • Sessions start on demand, persist state between calls, and recover from crashes — no manual management
  • Each project directory gets its own isolated Julia process
  • Pure stdio transport — no open ports or sockets

Tools

  • julia_eval(code, env_path?, timeout?) — execute Julia code in a persistent session. env_path sets the Julia project directory (omit for a temporary session). timeout defaults to 60s and is auto-disabled for Pkg operations.
  • julia_restart(env_path?) — restart a session, clearing all state. If env_path is omitted, restarts the temporary session.
  • julia_list_sessions — list active sessions and their status

Requirements

  • uv (you might already have it installed)
  • Julia – any version, julia binary must be in PATH
    • Recommended packages – used automatically if available in the global environment:
    • Revise.jl - to pick code changes up without restarting
    • TestEnv.jl — to properly activate test environment when env_path points to /test/

The server itself is written in Python since the Python MCP protocol implementation is very mature.

Usage

First, clone the repository:

cd /any_directory
git clone https://github.com/aplavin/julia-mcp.git

Then register the server with your client of choice (see below).

That's it! Your AI assistant can now execute Julia code more efficiently, saving of TTFX.

Claude Code

User-wide (recommended — makes Julia available in all projects):

claude mcp add --scope user julia -- uv run --directory /any_directory/julia-mcp python server.py

Project-scoped (only available in the current project):

claude mcp add --scope project julia -- uv run --directory /any_directory/julia-mcp python server.py

Append Julia flags after server.py to override the defaults (--startup-file=no --threads=auto):

claude mcp add --scope user julia -- uv run --directory /any_directory/julia-mcp python server.py --threads=1 --startup-file=yes

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "julia": {
      "command": "uv",
      "args": ["run", "--directory", "/any_directory/julia-mcp", "python", "server.py"]
    }
  }
}

Append Julia flags after server.py to override the defaults (--startup-file=no --threads=auto):

{
  "mcpServers": {
    "julia": {
      "command": "uv",
      "args": ["run", "--directory", "/any_directory/julia-mcp", "python", "server.py", "--threads=1", "--startup-file=yes"]
    }
  }
}

Codex CLI

User-wide — makes Julia available in all projects:

codex mcp add julia -- uv run --directory /any_directory/julia-mcp server.py

Append Julia flags after server.py to override the defaults (--startup-file=no --threads=auto):

codex mcp add julia -- uv run --directory /any_directory/julia-mcp server.py --threads=1 --startup-file=yes

VS Code Copilot

Add to .vscode/settings.json:

{
  "mcp": {
    "servers": {
      "julia": {
        "command": "uv",
        "args": ["run", "--directory", "/path/to/julia-mcp", "python", "server.py"]
      }
    }
  }
}

Append Julia flags after server.py to override the defaults (--startup-file=no --threads=auto):

{
  "mcp": {
    "servers": {
      "julia": {
        "command": "uv",
        "args": ["run", "--directory", "/path/to/julia-mcp", "python", "server.py", "--threads=1", "--startup-file=yes"]
      }
    }
  }
}

Details

  • Each unique env_path gets its own isolated Julia session. Omitting env_path uses a temporary session that is cleaned up on MCP shutdown.
  • If env_path ends in /test/, the parent directory is used as the project and TestEnv is activated automatically. For this to work, TestEnv must be installed in the base environment.
  • Julia is launched with --threads=auto and --startup-file=no by default. Pass custom Julia CLI flags after server.py to override these defaults entirely.

Alternatives

Other projects that give AI agents access to Julia:

  • MCPRepl.jl and REPLicant.jl require you to manually start and manage Julia sessions. julia-mcp handles this automatically.
  • DaemonConductor.jl (linux only) runs Julia scripts, but calls are independent and don't share variables. julia-mcp retains state between calls.

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Julia MCP

How do I install Julia MCP?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Julia MCP safe to use with an AI agent?

Its trust score is 39 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Julia MCP still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.