AIBase
EN
Explore
Starlark MCP
S

Starlark MCP

An MCP server based on the Starlark language, providing secure code execution capabilities for LLM clients, supporting the execution of Python-style scripts and returning execution results
Developer toolsEducation and learning tools#Code execution#Secure sandbox#Scripting language.Go
2 points
9.5K
Open Site

Overview

Content Details

Alternatives

What is the Starlark MCP Server?

The Starlark MCP Server is a code execution environment specifically designed for AI assistants. It is based on the Starlark language (a safe scripting language similar to Python), allowing AI models to generate code and execute it in a controlled environment, and then return the results to the AI assistant.

How to use the Starlark MCP Server?

After installing the server, AI assistants (such as Claude, Gemini) can call the execute_starlark tool through the MCP protocol to run code. The code execution results will be output through the print() function and returned to the AI assistant.

Applicable scenarios

Scenarios that require secure execution of AI-generated code, such as mathematical calculations, data processing, algorithm verification, prototype development, and educational demonstrations.

Main features

Secure code execution
Based on the sandbox environment of the Starlark language, ensuring the security and isolation of code execution
MCP protocol integration
Fully compatible with the Model Context Protocol and can be seamlessly integrated with various AI assistants
Extended built-in functions
Provides a rich library of built-in functions to enhance code execution capabilities
Output capture
Automatically captures the output of the print() function, supporting a maximum output content of 16KB
Advantages
Safe and reliable: Specifically designed for executing untrusted code
Easy to integrate: Supports mainstream AI assistants such as Claude and Gemini
Good performance: Developed based on the Go language with high execution efficiency
Developer-friendly: Python-like syntax with low learning cost
Limitations
Output limitation: Maximum output of 16KB, not suitable for processing large amounts of data
Language limitation: Only supports the Starlark language and does not support other programming languages
Function limitation: Compared with a complete programming environment, the built-in functions are limited

How to use

Install the server
Use the Go installation command to download and install the Starlark MCP Server
Register with the AI assistant
Register the server with the AI assistant you are using (Claude Code or Gemini)
Start using
Use the execute_starlark tool in the AI assistant to run Starlark code

Usage examples

Generate fractal images
Use Starlark code to generate mathematical fractal patterns, demonstrating code execution and visualization capabilities
Mathematical calculations
Perform complex mathematical operations or algorithm verification
Data processing
Perform simple processing, filtering, or conversion operations on data

Frequently Asked Questions

What is the difference between Starlark and Python?
Which AI assistants support this server?
Is there a time limit for code execution?
How to view code execution errors?

Related resources

MCP official documentation
Official documentation and specifications of the Model Context Protocol
Starlark language documentation
Official documentation and syntax reference for the Starlark programming language
Built-in function documentation
List and usage of extended built-in functions of the Starlark MCP Server
Project code repository
Source code and latest version of the Starlark MCP Server

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

Alternatives

V
Vestige
Vestige is an AI memory engine based on cognitive science. By implementing 29 neuroscience modules such as prediction error gating, FSRS - 6 spaced repetition, and memory dreaming, it provides long - term memory capabilities for AI. It includes a 3D visualization dashboard and 21 MCP tools, runs completely locally, and does not require the cloud.
Rust
9.2K
4.5 points
M
Moltbrain
MoltBrain is a long-term memory layer plugin designed for OpenClaw, MoltBook, and Claude Code, capable of automatically learning and recalling project context, providing intelligent search, observation recording, analysis statistics, and persistent storage functions.
TypeScript
8.7K
4.5 points
B
Bm.md
A feature-rich Markdown typesetting tool that supports multiple style themes and platform adaptation, providing real-time editing preview, image export, and API integration capabilities
TypeScript
14.6K
5 points
S
Security Detections MCP
Security Detections MCP is a server based on the Model Context Protocol that allows LLMs to query a unified security detection rule database covering Sigma, Splunk ESCU, Elastic, and KQL formats. The latest version 3.0 is upgraded to an autonomous detection engineering platform that can automatically extract TTPs from threat intelligence, analyze coverage gaps, generate SIEM-native format detection rules, run tests, and verify. The project includes over 71 tools, 11 pre-built workflow prompts, and a knowledge graph system, supporting multiple SIEM platforms.
TypeScript
7.7K
4 points
P
Paperbanana
Python
8.8K
5 points
B
Better Icons
An MCP server and CLI tool that provides search and retrieval of over 200,000 icons, supports more than 150 icon libraries, and helps AI assistants and developers quickly obtain and use icons.
TypeScript
10.4K
4.5 points
A
Assistant Ui
assistant - ui is an open - source TypeScript/React library for quickly building production - grade AI chat interfaces, providing composable UI components, streaming responses, accessibility, etc., and supporting multiple AI backends and models.
TypeScript
9.7K
5 points
A
Apify MCP Server
The Apify MCP Server is a tool based on the Model Context Protocol (MCP) that allows AI assistants to extract data from websites such as social media, search engines, and e-commerce through thousands of ready-to-use crawlers, scrapers, and automation tools (Apify Actors). It supports OAuth and Skyfire proxy payment and can be integrated into MCP clients such as Claude and VS Code through HTTPS endpoints or local stdio.
TypeScript
10.5K
5 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
23.4K
4.5 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
38.7K
5 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
79.5K
4.3 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
26.9K
4.3 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
38.0K
5 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
71.2K
4.5 points
G
Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
23.7K
4.5 points
C
Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
105.7K
4.7 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
English简体中文繁體中文にほんご
© 2026AIBase