What security measures does Container-MCP use?
It uses container isolation via Podman/Docker, AppArmor profiles, Firejail sandboxing, resource limits (CPU, memory, execution time), path traversal prevention, and allowed extension restrictions.
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Basic information
A podman ubuntu 24.04 container that serves a MCP server; with file, code execution, bash shell, knowledgebase, and more.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"container-mcp": {
"content": "This is the content of the web page...",
"url": "https://example.com/page",
"title": "Example Page",
"success": true,
"error": null
}
}
}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.
Fetch the live tool list directly from this server's endpoint using the button above.
Container-MCP is a secure, container-based implementation of the Model Context Protocol (MCP) that provides a sandboxed environment for executing code, running commands, accessing files, and performing web operations on behalf of large language models. It exposes these capabilities as standardized tools that AI systems can discover and call.
Configure the server via environment variables and run it in development or production mode. Tools are discovered and called by AI systems using the MCP protocol. No explicit installation or invocation commands are documented in the README.
It uses container isolation via Podman/Docker, AppArmor profiles, Firejail sandboxing, resource limits (CPU, memory, execution time), path traversal prevention, and allowed extension restrictions.
Managers include BashManager, PythonManager, FileManager, WebManager, KnowledgeBaseManager, ListManager, MarketManager (Yahoo Finance), and RssManager.
Yes, `web_browse` requires Playwright browser binaries. Outside the container, install them with `python -m playwright install chromium` (or `playwright install`).
Documents use a structured URI format (`kb://namespace/collection[/subcollection]*/name`) and support RDF-style relationships, preferences, references, and metadata management.
Yes, extensive configuration via environment variables is supported, including custom environment and switching between development and production modes.
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