E2B MCP Server

What does “E2B” MCP Server do?

The E2B MCP (Model Context Protocol) Server is a tool designed to empower AI assistants—most notably Claude—with the ability to execute code in a secure, isolated environment via the E2B Sandbox. By integrating with external systems through the MCP, E2B enables AI agents to perform dynamic computational tasks, such as running code, managing files, or interfacing with APIs. This enhances development workflows by allowing LLMs to take real-world actions, analyze code, and automate complex processes that require code execution beyond the capabilities of standard chat-based models. The server is available in both JavaScript and Python editions and is optimized for integration with tools like Claude Desktop, thereby extending the agent’s utility in areas like data analysis, rapid prototyping, and automated testing.

List of Prompts

No information found in the repository about specific prompt templates provided by the E2B MCP Server.

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List of Resources

No information found in the repository about specific resources exposed by the E2B MCP Server.

List of Tools

No specific tools are listed in the root README or visible code files. The server’s main functionality is to enable code execution, but detailed tool descriptions are not provided in the available documentation.

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Use Cases of this MCP Server

• Code Execution for AI Agents: Enables AI models like Claude to run code snippets on demand, supporting data analysis, prototyping, and computational tasks directly from chat interfaces.
• Secure Sandbox Environment: Provides a safe, isolated space for executing potentially untrusted code, mitigating risks for developers and users.
• Development Automation: Facilitates automation of testing, code validation, or deployment tasks by integrating programmable code execution into developer workflows.
• Enhanced AI Interactions: Allows AI assistants to move beyond static responses by performing real-world actions, analyzing outputs, and iterating solutions programmatically.

How to set it up

Windsurf

1. Ensure Node.js is installed on your machine.
2. Locate your Windsurf configuration file.
3. Add the E2B MCP Server to the mcpServers section using the following JSON:

   {
     "e2b": {
       "command": "npx",
       "args": ["@e2b-dev/mcp-server@latest"]
     }
   }
   

4. Save the configuration file and restart Windsurf.
5. Verify the server is running by checking the Windsurf logs or MCP integrations panel.

Claude

1. Install Node.js if not already present.
2. Open the Claude Desktop settings or configuration file.
3. Insert the E2B MCP Server into the mcpServers section:

   {
     "e2b": {
       "command": "npx",
       "args": ["@e2b-dev/mcp-server@latest"]
     }
   }
   

4. Save your changes and restart the Claude Desktop app.
5. Confirm integration by accessing the AI agent’s tool list.

Cursor

1. Make sure Node.js is installed.
2. Find the Cursor app’s configuration file.
3. Add the following entry to the mcpServers section:

   {
     "e2b": {
       "command": "npx",
       "args": ["@e2b-dev/mcp-server@latest"]
     }
   }
   

4. Save and restart the Cursor application.
5. Validate by checking the available MCP tools.

Cline

1. Install Node.js as a prerequisite.
2. Navigate to the Cline configuration file.
3. Append the E2B MCP Server config:

   {
     "e2b": {
       "command": "npx",
       "args": ["@e2b-dev/mcp-server@latest"]
     }
   }
   

4. Save and restart Cline.
5. Ensure the MCP server is accessible via Cline’s interface.

Securing API Keys using Environment Variables

To securely provide API keys or other secrets, use environment variables in your configuration:

{
  "e2b": {
    "command": "npx",
    "args": ["@e2b-dev/mcp-server@latest"],
    "env": {
      "API_KEY": "${E2B_API_KEY}"
    },
    "inputs": {
      "apiKey": "${E2B_API_KEY}"
    }
  }
}

Replace "API_KEY" and "E2B_API_KEY" with your actual environment variable names as needed.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "e2b": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change "e2b" to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the tables, the E2B MCP Server provides a robust overview and clear setup instructions. However, the lack of detailed documentation on prompts, resources, and explicit tools limits its utility for advanced customization without further exploration of the codebase. The project is well-maintained with open-source licensing and a good level of community engagement.

MCP Score