Nebula API

from openai import OpenAI

client = OpenAI(
    api_key="bl_live_xxxxxxxxxxxx",
    base_url="https://api.breachline.io/api/v1/llm"
)

# Define security tools
tools = [
    {
        "type": "function",
        "function": {
            "name": "scan_target",
            "description": "Perform a security scan on a target",
            "parameters": {
                "type": "object",
                "properties": {
                    "target": {"type": "string", "description": "URL or IP to scan"},
                    "scan_type": {"type": "string", "enum": ["quick", "full", "stealth"]}
                },
                "required": ["target"]
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "lookup_cve",
            "description": "Look up CVE details",
            "parameters": {
                "type": "object",
                "properties": {
                    "cve_id": {"type": "string", "description": "CVE ID (e.g., CVE-2024-1234)"}
                },
                "required": ["cve_id"]
            }
        }
    }
]

response = client.chat.completions.create(
    model="nebula-pro",
    messages=[{"role": "user", "content": "Scan example.com for vulnerabilities"}],
    tools=tools,
    tool_choice="auto"
)

# Handle tool calls
if response.choices[0].message.tool_calls:
    for tool_call in response.choices[0].message.tool_calls:
        print(f"Tool: {tool_call.function.name}")
        print(f"Args: {tool_call.function.arguments}")

import asyncio
import websockets
import json

async def stream_chat():
    uri = "wss://api.breachline.io/api/v1/ws"

    async with websockets.connect(uri, extra_headers={
        "X-API-Key": "bl_live_xxxxxxxxxxxx"
    }) as ws:
        # Send a chat message
        await ws.send(json.dumps({
            "type": "chat",
            "model": "nebula-pro",
            "messages": [
                {"role": "user", "content": "Write a security audit report for example.com"}
            ]
        }))

        # Receive streaming chunks
        async for message in ws:
            data = json.loads(message)
            if data.get("type") == "chunk":
                print(data["content"], end="", flush=True)
            elif data.get("type") == "done":
                print("\n[Stream complete]")
                break

asyncio.run(stream_chat())

// MCP Configuration (claude_desktop_config.json)
{
  "mcpServers": {
    "nebula": {
      "command": "npx",
      "args": ["-y", "@breachline/mcp-server"],
      "env": {
        "NEBULA_API_KEY": "bl_live_xxxxxxxxxxxx",
        "NEBULA_BASE_URL": "https://api.breachline.io/api/v1/llm"
      }
    }
  }
}

// Use with MCP SDK
import { Client } from "@modelcontextprotocol/sdk/client/index.js";

const client = new Client({ name: "my-app", version: "1.0.0" });
await client.connect(transport);

const result = await client.callTool({
  name: "nebula_chat",
  arguments: {
    model: "nebula-pro",
    message: "Analyze security headers for example.com"
  }
});

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