Rubiscout Email Analysis MCP Server
by raj-rubicon
README.md
# rubiscout-mcp
MCP server for [Rubiscout](https://rubiscout.com) — AI-powered email header analysis for phishing, spoofing, and BEC detection. Exposes Rubiscout's forensic analysis as tools for Claude Code, Claude Desktop, Cursor, and any other MCP-compatible agent.
## Install
```bash
npx rubiscout-mcp
```
Or install globally:
```bash
npm install -g rubiscout-mcp
```
## Configuration
Get a free API key at [rubiscout.com/dashboard](https://rubiscout.com/dashboard), then add to your MCP client config (e.g. `~/.claude/settings.json` or Claude Desktop config):
```json
{
"mcpServers": {
"rubiscout": {
"command": "npx",
"args": ["-y", "rubiscout-mcp"],
"env": {
"RUBISCOUT_API_KEY": "rbs_live_..."
}
}
}
}
```
Alternatively, set `RUBISCOUT_API_KEY` as a system environment variable and omit the `env` block.
## Tools
| Tool | Description |
|---|---|
| `analyze_email` | Submit a raw email string for full forensic analysis. Returns verdict, risk score, authentication results (SPF/DKIM/DMARC/ARC), IP reputation, routing trace, and recommendations. |
| `get_analysis` | Retrieve a previously stored analysis by UUID. |
| `list_analyses` | List recent analyses, optionally filtered by risk score. |
## Example usage
Once configured, ask your agent directly:
> "Analyze this email for me and tell me if it's a phishing attempt" [paste email]
> "Get my last 5 analyses and summarize the threat patterns"
> "Analyze all .eml files in this directory and flag any Critical or High risk ones"
## Development
```bash
npm install
npm run build
npm start
```
## Docker
```bash
docker build -t rubiscout-mcp .
docker run -i -e RUBISCOUT_API_KEY=rbs_live_... rubiscout-mcp
```
## Links
- [Full documentation](https://rubiscout.com/docs#mcp)
- [REST API reference](https://rubiscout.com/api-reference)
- [Get an API key](https://rubiscout.com/dashboard)
## License
MIT
TDQS
A4.1/5.0
Scored across 3 tools
Disambiguation5/5
Each tool targets a distinct operation: analyzing a new email, retrieving a specific analysis by UUID, and listing recent analyses. There is no functional overlap.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with lowercase and underscores (analyze_email, get_analysis, list_analyses), making them predictable.
Tool Count4/5
With 3 tools, the server is scoped tightly to email analysis. While minimal, it covers the primary use cases without unnecessary bloat.
Completeness4/5
The server provides core CRUD-like operations (create, read, list) for email analyses. Missing update and delete are minor gaps, but the essential workflow for analysis is complete.
Maintenance
ActivityStale
ResponsivenessNo issues