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DockaShell MCP Server

@anzax

Repository

Basic information

Category

Other

License

Apache-2.0

Transports

stdio

Author

anzax

Submitted by

anzax

About DockaShell MCP Server

DockaShell is an MCP server that gives AI agents isolated Docker containers to work in. MCP tools for shell access, file operations, and full audit trail.

#agent#docker#mcp#model-context-protocol#vibe-coding#coding-agent

DockaShell MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "dockashell": {
      "command": "dockashell",
      "args": [
        "serve"
      ]
    }
  }
}

DockaShell MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is DockaShell?

DockaShell is an MCP (Model Context Protocol) server that gives AI agents isolated Docker containers to work in. Each agent gets its own persistent environment with shell access, file operations, and full audit trails.

How to use DockaShell?

Install globally with npm install -g dockashell, then run dockashell build, dockashell create my-project, and dockashell start my-project. Add the server to your MCP client configuration using command dockashell with args ["serve"]. Requires Node.js 20+ and Docker running.

Key features of DockaShell

  • Shell-based workflows instead of specialized tools
  • Container isolation for host system safety
  • Persistent workspace surviving across sessions
  • Complete audit trail for every command
  • Self-evolving agents building their own tools
  • Autonomous exploration without constant approval

Use cases of DockaShell

  • Data analysis with Python environment and CSV processing
  • Web development building React apps with live preview
  • Research assistant with persistent SQLite databases
  • Meta-learning by analyzing previous traces to improve

Frequently asked questions

1

What problems does DockaShell solve?

It addresses no persistent memory, tool babysitting, limited toolsets, and lack of self-reflection in current AI assistants.

2

How does it ensure security?

Each agent runs in an isolated Docker container, giving full autonomy inside with zero risk to the host system.

3

What are the requirements?

Node.js 20+ and a running Docker engine.

4

Can agents persist data across sessions?

Yes, each container uses a persistent volume so files, databases, and context survive between sessions.

Comments

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