What dependencies are required?
Ollama must be installed and its URL configured in the client initializations. The project uses `uv` for package and environment management.
@SirAppSec
基本信息
MCP Security Playground - Hack with MCP Servers, MCP Clients. Try out different vulnerabilities and abuse LLMs and agents in a UI friendly experimentation lab
工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
It is an experimental sandbox and lab for exploring MCP hosts, clients, and servers. It can perform attacks against MCP servers and abuse LLMs.
Install dependencies using uv install, create a virtual environment with uv venv, activate it, then run the server with uv run -- src/mcp-security-sandbox/mcp/github/server.py and launch the Streamlit frontend with streamlit run src/mcp-security-sandbox/frontend/MCP_Chat.py. Ensure Ollama is installed and its URL is set in the client initializations.
Ollama must be installed and its URL configured in the client initializations. The project uses `uv` for package and environment management.
Run `uv install`, `uv venv`, `source .venv/bin/activate`, then `uv run -- src/mcp-security-sandbox/mcp/github/server.py` and `streamlit run src/mcp-security-sandbox/frontend/MCP_Chat.py`.
No, dynamic loading is on the roadmap but not yet implemented; currently servers are statically defined.
It is an experimental sandbox for exploring MCP hosts, clients, and servers, and for performing attacks against MCP servers and abusing LLMs.
Yes, the README shows using Burp Suite MCP Server to
Model Context Protocol (MCP) server for TranscriptFetch: fetch YouTube transcripts, search, channels, and playlists from any MCP client.

Agent-Native Terminal

One case file per task — shared by every session, agent and person that touches it. Self-hosted MCP server and live board. MIT.
Set up and manage the Eddyter AI rich text editor by talking to your AI agent — for Claude, Cursor, Codex and other MCP tools. A Model Context Protocol server that lets AI tools add Eddyter to a React, Next.js, Vite or R

Know when your AI agents, cron jobs and CI pipelines fail, stall or go quiet. Your agent sets up monitors from a plain description, tells you what is broken and why, reads run history and traces, and writes notes on inci
评论