An MCP (Model Context Protocol) guardrail with built-in AI-powered moderation that aggregates multiple MCP servers into one secure interface.
The MCP Guardrail provides AI-powered security and easy configuration for your MCP (Model Context Protocol) setup. It automatically detects your existing MCP configuration files and adds a protective layer with intelligent moderation capabilities.
Key features:
- AI-powered moderation to prevent prompt injection attacks
- Automatic configuration - CLI tool detects and updates MCP config files for Cursor, Claude Desktop, and Claude Code
- Dual connectivity - supports both local and remote MCP servers
- Transparent proxying - tools, prompts, and resources are automatically prefixed and made available
The easiest way to get started is using the General Analysis CLI tool:
# Install the CLI tool
pip3 install generalanalysis==0.1.7
# Login to your account
ga login
# Configure MCP settings for Cursor, Claude Desktop, and Claude Code
ga configure
This will automatically update your MCP configuration files with the guardrail setup.
graph LR
A[MCP Client] --> B[MCP Guard]
B --> C[MCP Server]
C --> D[Tool Output]
D --> B
B --> E{GA Guardrail}
E -->|Safe| A
E -->|Blocked| F[Alert]
No installation required! Use directly in your Cursor or Claude Desktop MCP configuration:
{
"mcpServers": {
"protected_server": {
"command": "npx",
"args": [
"-y",
"@general-analysis/mcp-guard",
"[{\"name\":\"server1\",\"command\":\"path/to/server\",\"args\":[\"arg1\"]}]"
]
}
}
}
npx -y @general-analysis/mcp-guard '[{"name":"server1","command":"path/to/server","args":["arg1"]}]'
For local MCP servers that communicate via stdio:
{
"mcpServers": {
"protected_server": {
"command": "npx",
"args": [
"-y",
"@general-analysis/mcp-guard",
"[{\"name\":\"my-local-server\",\"command\":\"node\",\"args\":[\"path/to/server.js\"]}]"
],
"env": {
"API_KEY": "your-general-analysis-api-key",
"ENABLE_GUARD_API": "true"
}
}
}
}
For remote MCP servers accessible via HTTP or Server-Sent Events:
{
"mcpServers": {
"protected_server": {
"command": "npx",
"args": [
"-y",
"@general-analysis/mcp-guard",
"[{\"name\":\"my-remote-server\",\"url\":\"https://api.example.com/mcp\"}]"
],
"env": {
"API_KEY": "your-general-analysis-api-key",
"ENABLE_GUARD_API": "true"
}
}
}
}
API_KEY
- Your General Analysis API key for the moderation serviceENABLE_GUARD_API
- Set to"true"
to enable AI-powered moderation (requires API_KEY)
Add this to your MCP configuration file:
{
"mcpServers": {
"guardrail": {
"command": "npx",
"args": [
"-y",
"@general-analysis/mcp-guard",
"[{\"name\":\"local-filesystem\",\"command\":\"npx\",\"args\":[\"@modelcontextprotocol/server-filesystem\",\"/path/to/files\"]},{\"name\":\"remote-api\",\"url\":\"https://api.example.com/mcp\"}]"
],
"env": {
"API_KEY": "your-general-analysis-api-key",
"ENABLE_GUARD_API": "true"
}
}
}
}
# Set environment variables
export API_KEY="your-general-analysis-api-key"
export ENABLE_GUARD_API="true"
# Run with mixed local and remote servers
npx -y @general-analysis/mcp-guard '[
{
"name": "local-filesystem",
"command": "npx",
"args": ["@modelcontextprotocol/server-filesystem", "/path/to/files"]
},
{
"name": "remote-api",
"url": "https://api.example.com/mcp"
}
]'
- Node.js >= 18.0.0
- Valid General Analysis API key (when moderation is enabled)
MIT