Optix MCP Server

@AdamWaldie

代码仓库

基本信息

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其他

传输方式

stdio

作者

AdamWaldie

提交者

adam waldie

关于 Optix MCP Server

暂无概览

Optix MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "OPTIX-MCP": {
      "command": "python",
      "args": [
        "main.py"
      ]
    }
  }
}

Optix MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Optix?

Optix is a standalone Python/FastAPI server that implements the Model Context Protocol (MCP) for the OPTIX threat intelligence platform. It exposes 26 analyst-friendly tools that AI assistants and programmatic consumers can use to query threat feeds, search documents and indicators, manage watchlists, triage IOCs, generate detection rules, trigger AI research, and produce intelligence reports without needing to understand OPTIX's internal REST API.

How to use Optix?

Deploy the server locally: requires Python 3.11+, an active OPTIX installation, and an OPTIX API key. Set environment variables (e.g., OPTIX_API_URL, MCP_PORT) in a .env file or shell, install dependencies with pip install -r requirements.txt, then run python main.py. Connect AI clients like Claude Desktop or Cursor using the provided configuration snippets (Smithery for hosted mode, or self-hosted via HTTP SSE or stdio). All tool requests authenticate via the X-API-Key header.

Key features of Optix

26 tools across Read, Write, and AI categories.
Credit system with pre-flight balance checks.
Supports threat feed queries, IOC search, document retrieval.
AI-powered entity research and report generation.
Watchlist management with notifications.
Integration with Claude Desktop and Cursor via MCP.

Use cases of Optix

A SOC analyst asks "What are the latest critical threats?" and retrieves a curated threat feed.
An AI assistant searches for a specific IOC such as an IP or hash across OPTIX intelligence.
An incident responder submits a structured incident report and receives a tactical intelligence report.
A detection engineer generates Sigma or YARA rules for a specific malware family.
A threat hunter queries the ATT&CK coverage matrix to identify detection gaps.

常见问题

What are the dependencies and runtime requirements?

Python 3.11+, an active OPTIX installation, and an OPTIX API key are required. The server uses FastAPI and requires packages listed in `requirements.txt`.

How is authentication handled?

Every request to the MCP endpoint must include the OPTIX API key in the `X-API-Key` header. Unauthenticated requests receive a structured 401 response.

Where does the data live?

All data resides in the OPTIX backend. The MCP server acts as a proxy; it does not store any intelligence data locally.

What transport protocols are supported?

The server supports HTTP SSE (Server-Sent Events) on the `/mcp` endpoint and stdio mode for local execution (see Claude Desktop config). A health check is available at `GET /health`.

Are there any usage limits or costs?

Several tools consume OPTIX credits (e.g., `report_incident` costs 40 credits, `research_entity` costs 15 credits). The server performs a pre-flight credit check before any credit-consuming call, and free tools such as `get_threat_feed` and `search_indicator` have no credit cost.

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