julia-mcp
Active·★ 65·MIT·Updated 2026-05-16
★ Trending★ Memory & Context
MCP server for persistent Julia sessions — fast iteration without startup/compilation overhead
Julia-mcp is an MCP server designed to provide AI assistants with efficient access to Julia code execution. It optimizes performance by maintaining persistent Julia sessions, avoiding startup and compilation overheads, and preserving state across calls for faster iterative execution.
#AI Assistants#Julia#MCP Protocol#Persistent Sessions#Code Execution#Performance Optimization#State Management#Python
01
Features
01Persistent Julia sessions with state preservation between calls.
02Automatic session management, including on-demand start and crash recovery.
03Isolated Julia processes for each project directory.
04Efficient code execution for AI assistants by reducing Julia's startup and compilation costs.
02
Compatibility
Julia
Runtime
Verified via docs
Python
Server Runtime
Verified via docs
uv
Dependency
Verified via docs
Claude
AI Client Integration
Verified via docs
Codex CLI
AI Client Integration
Verified via docs
VS Code Copilot
AI Client Integration
Verified via docs
03
Quick start
1
$ git clone https://github.com/aplavin/julia-mcp.git
04
Use cases
↳Empowering AI assistants with efficient and stateful Julia code execution capabilities.
↳Accelerating iterative development and analysis workflows that rely on Julia, by minimizing TTFX.
↳Integrating Julia programming and computational power seamlessly into various AI client environments like Claude, Codex, or VS Code Copilot.
05
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Comments
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- RRemy LewisMay 16, 2026
Persistent Julia sessions via MCP eliminate the startup overhead that makes Julia iteration slow
- FFinley JohnsonApr 28, 2026
Fast iteration without recompilation is the key productivity gain for Julia development
- MMarlowe NguyenApr 2, 2026
Used for scientific computing workflows, the session persistence is a major time saver
- EEmerson DavisMar 21, 2026
The MCP integration means Julia capabilities are available alongside other tools