document Claude MCP usage in README

Closes #193

Expands the MCP server section with:
- what tools are exposed and what each one does
- step-by-step Claude Desktop setup
- the three built-in prompt templates and when to use them
- a short example conversation showing natural-language scan control
- Claude Code CLI setup for terminal-based workflows
This commit is contained in:
Yash Dhawan
2026-05-15 10:25:06 +05:30
parent 0086895db1
commit 8e3120c90d
+53
View File
@@ -403,6 +403,10 @@ The `Module` class is designed to manage prompt processing and interaction with
## MCP server
The Agentic Security MCP server exposes the scanner's REST API as callable tools and reusable prompt templates, so any MCP-compatible client (Claude Desktop, Claude Code, custom agents) can drive security scans through natural language.
### Installation
```shell
pip install -U mcp
@@ -410,6 +414,55 @@ pip install -U mcp
mcp install agentic_security/mcp/main.py
```
### Using with Claude Desktop
1. Start the Agentic Security FastAPI server (default port `8718`):
```shell
poetry run agentic_security
```
2. Install the MCP server into Claude Desktop:
```shell
mcp install agentic_security/mcp/main.py --name "Agentic Security"
```
3. Open Claude Desktop — the following **tools** are now available:
| Tool | Description |
|---|---|
| `start_scan` | Launch a security scan against an LLM spec |
| `stop_scan` | Halt an in-progress scan |
| `verify_llm` | Check that an LLM spec is reachable |
| `get_data_config` | Retrieve the current dataset configuration |
| `get_spec_templates` | List available LLM spec templates |
4. Or kick off a scan using one of the built-in **prompt templates**:
- **`security_scan_prompt`** — runs a full scan with a configurable probe budget
- **`verify_llm_prompt`** — confirms a spec is reachable before committing to a scan
- **`adversarial_probe_prompt`** — enables multi-step attacks and asks Claude to summarise the worst findings
### Example conversation with Claude
```
You: Use the security_scan_prompt for spec "openai/gpt-4o" with a budget of 500 probes.
Claude: I'll kick off the scan now. Starting with verify_llm to confirm the spec is
reachable, then launching start_scan with maxBudget=500...
```
### Using with Claude Code (CLI)
```shell
# Add to your project's MCP config
claude mcp add agentic-security -- python agentic_security/mcp/main.py
# Then interact inline
claude "Run a quick adversarial probe against my local LLM at http://localhost:8080/v1"
```
## Documentation
For more detailed information on how to use Agentic Security, including advanced features and customization options, please refer to the official documentation.