AI Skill Hub 强烈推荐:蜂蜜MCP 是一款优质的MCP工具。AI 综合评分 8.0 分,在同类工具中表现稳健。如果你正在寻找可靠的MCP工具解决方案,这是一个值得深入了解的选择。
蜂蜜MCP 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
蜂蜜MCP 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/barvhaim/HoneyMCP
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"--mcp": {
"command": "npx",
"args": ["-y", "honeymcp"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 蜂蜜MCP 执行以下任务... Claude: [自动调用 蜂蜜MCP MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"__mcp": {
"command": "npx",
"args": ["-y", "honeymcp"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
<img src="https://github.com/user-attachments/assets/34f18118-1490-4f06-af08-f2efb0ecec79" alt="HoneyMCP logo" width="300" height="300" />
Detect AI Agent Attacks Through Deception
HoneyMCP is a defensive security tool that adds deception capabilities to Model Context Protocol (MCP) servers. It injects "ghost tools" (fake security-sensitive tools) that act as honeypots, detecting two critical threat categories:
One line of code. High-fidelity detection. Complete attack telemetry.
---
pip install honeymcp
honeymcp init # Creates config files This creates the following config files: - honeymcp.yaml - Ghost tool configuration - .env.honeymcp - LLM credentials (only needed for dynamic ghost tools)
HoneyMCP injects deceptive security-sensitive tools that appear alongside legitimate tools:
Two Modes:
Dynamic Mode (Default) - LLM analyzes your server context and generates domain-specific honeypots: - File server → bypass_file_permissions, read_system_credentials - Database server → dump_admin_credentials, bypass_query_restrictions - API gateway → list_internal_api_keys, access_admin_endpoints
Static Mode - Pre-configured generic honeypots: - list_cloud_secrets, execute_shell_command, read_private_files
The easiest way to configure HoneyMCP: ```bash honeymcp init # Creates honeymcp.yaml + .env.honeymcp
Dynamic ghost tools require LLM credentials. Run honeymcp init to generate .env.honeymcp, then add your credentials:
Add to .env.honeymcp:
LLM_PROVIDER=openai
LLM_MODEL=gpt-4o-mini
OPENAI_API_KEY=your_key_here
Supported providers: - LLM_PROVIDER=openai: Requires OPENAI_API_KEY - LLM_PROVIDER=watsonx: Requires WATSONX_URL, WATSONX_APIKEY, WATSONX_PROJECT_ID - LLM_PROVIDER=ollama: Requires OLLAMA_API_BASE (default: http://localhost:11434)
HoneyMCP loads .env.honeymcp first, then falls back to .env. This keeps HoneyMCP credentials separate from your project's environment.
Add HoneyMCP to your FastMCP server with one line:
```python from fastmcp import FastMCP from honeymcp import honeypot
mcp = FastMCP("My Server")
@mcp.tool() def my_real_tool(data: str) -> str: """Your legitimate tool""" return f"Processed: {data}"
honeymcp create-tool "dump container registry credentials"
ToolGen automatically: - Determines tool category (exfiltration, bypass, privilege escalation) - Infers threat level from description keywords - Extracts parameters and types - Generates realistic response templates - Adds tool to both ghost_tools.py and middleware.py - Validates all generated code
$ honeymcp create-tool "list terraform state files with secrets"
✅ Tool created: list_terraform_state
Category: exfiltration
Threat Level: critical
📝 Agent Reasoning:
- Analyzing tool description to extract specifications
- Generating response generator function
- Validating generated response function
- Checking code quality and security
The new tool is immediately available in your honeypot catalog.
---
git clone https://github.com/barvhaim/HoneyMCP.git
cd HoneyMCP
uv sync
Static ghost tools demo:
MCP_TRANSPORT=sse uv run python examples/demo_server.py
Dynamic ghost tools demo (requires LLM credentials in .env.honeymcp):
MCP_TRANSPORT=sse uv run python examples/demo_server_dynamic.py
honeymcp clean-data ```
```yaml
HoneyMCP also supports environment overrides:
HONEYMCP_EVENT_PATH - overrides the base event storage directoryfrom pathlib import Path
from honeymcp import honeypot, ProtectionMode
mcp = honeypot(
mcp,
# Dynamic ghost tools (default)
use_dynamic_tools=True, # LLM-generated domain-specific tools
num_dynamic_tools=3, # Number of dynamic tools to generate
fallback_to_static=True, # Use static tools if LLM fails
# Static ghost tools (optional)
ghost_tools=["list_cloud_secrets", "execute_shell_command"],
# Protection mode (default: SCANNER)
protection_mode=ProtectionMode.SCANNER, # or ProtectionMode.COGNITIVE
# Other settings
event_storage_path=Path.home() / ".honeymcp" / "events",
enable_dashboard=True,
)
Dynamic vs Static Tools: - Dynamic (default): LLM analyzes your server and generates relevant honeypots (requires LLM credentials in .env.honeymcp) - Static: Pre-defined generic tools (no LLM required, set use_dynamic_tools=False)
---
For stdio transport (recommended - works with all Claude Desktop versions):
Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"honeymcp-demo": {
"command": "uv",
"args": ["run", "python", "/path/to/HoneyMCP/examples/demo_server.py"],
"env": {"MCP_TRANSPORT": "stdio"}
}
}
}
If your client does not support an env block, launch the server with MCP_TRANSPORT=stdio in your shell.
For Streamable HTTP transport (requires Claude Pro/Max/Team/Enterprise):
1. Start the server:
MCP_TRANSPORT=http uv run python examples/demo_server.py
2. Configure Claude Desktop:
{
"mcpServers": {
"honeymcp-demo": {
"url": "http://localhost:8000/mcp"
}
}
}
高质量的MCP安全工具,值得使用
该工具使用 NOASSERTION 协议,商用场景请仔细阅读协议条款,必要时咨询法律意见。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
📄 NOASSERTION — 请查阅原始协议条款了解具体使用限制。
总体来看,蜂蜜MCP 是一款质量优秀的MCP工具,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | HoneyMCP |
| Topics | mcphoneypotpython |
| GitHub | https://github.com/barvhaim/HoneyMCP |
| License | NOASSERTION |
| 语言 | Python |
收录时间:2026-05-28 · 更新时间:2026-05-28 · License:NOASSERTION · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端