Code Execution Server

Code Execution Server

Enables execution of code in a sandbox environment with integrated web search capabilities. Provides a basic framework for running code safely, primarily designed for AI agents and research applications.

Category
Visit Server

README

Code Execution Server

This repository provides a basic implementation of a code execution server, designed primarily for Xmaster (paper, code) and Browse Master (paper code). The full implementation is used in SciMaster.

Due to the proprietary nature of the full code, this repository only includes an open-source framework and the basic components required for code execution. It also includes a simple network search tool implementation.

⚠️ Warning: This is a basic code execution server without virtualization or safety protections. For added security, consider running it within Docker or Apptainer containers as necessary.


🛠️ Setup

Environment

Clone this repository and navigate to the project directory and install the required dependencies:

cd mcp_sandbox/
pip install -r requirements.txt

Tools

  • setup the serper key in configs/web_agent.json
  • setup the models' api key in configs/llm_call.json

🚀 Deploy the Code Execution Server

Step 1: Start the API Server

We will first start the API server used by the tools. This API server proxies all search-related services, including:

  • Serper's Google Search Service
  • A series of Model APIs

Navigate to the api_proxy directory and start the API server:

cd api_proxy
python api_server.py

Step 2: Deploy the Server

Deploy the server by running the following script in the MCP directory:

cd MCP
bash deploy_server.sh

📝 Usage

Sending a Request

To send a request to the server, use the following curl command:

curl -X POST "http://<your-server-url>/execute" \
     -H "Content-Type: application/json" \
     -d '{"code": "<your code here>"}'

⚡ Benchmarking

For benchmarking, you can run the following command to test the server's performance:

bash benchmarking/pressure.sh 100 100 10 benchmarking/script.lua http://127.0.0.1:30008

Example output:

Running 10s test @ http://127.0.0.1:30008/execute
  100 threads and 100 connections
  Thread Stats   Avg      Stdev     Max   +/- Stdev
    Latency    50.21ms   47.15ms 296.96ms   53.20%
    Req/Sec    24.13     13.58   130.00     54.99%
  23185 requests in 10.10s, 4.27MB read
Requests/sec:   2295.61
Transfer/sec:    432.74KB

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured