dedicated isolated environment for your AI agent
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"mcp-code-executor-server": {
"command": "<see-readme>",
"args": []
}
}
}Are you the author?
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A robust Model Context Protocol (MCP) server that enables AI agents to execute code across multiple programming languages in a secure, isolated environment.
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A robust Model Context Protocol (MCP) server that enables AI agents to execute code across multiple programming languages in a secure, isolated environment.
MCP Code Executor Server standardizes how AI models connect to various programming runtimes by exposing a unified MCP tool endpoint. It allows AI assistants to:
The MCP Code Executor Server follows a client-server model:

Clone the repository:
git clone https://github.com/yourusername/mcp-code-executor-server.git
cd mcp-code-executor-server
Build & Run:
# Build the project
./mvnw clean package
# Start the server
./mvnw spring-boot:run
The server listens on port 8080 by default.
For isolation, run in Docker:
# Build Docker image
docker build -t mcp-code-executor .
# Run container
docker run -p 8080:8080 mcp-code-executor
Or with Docker Compose:
docker-compose up -d
http://localhost:8080.code-execution tool.Example MCP request:
{
"language": "python",
"code": "print('Hello, world!')\nprint('hello again')"
}
Contributions are welcome!.
Apache License 2.0. See the LICENSE file for details.