---
repository: "fastly-sigsci-edge-mcp"
primary_technology: ["Platform", "Signal Sciences", "MCP"]
use_case: "Automated Security Operations Sync and Querying"
agent_intent_tags: ["MCP Server", "Signal Sciences", "Security Automation", "AI Agents"]
---

# Repository Summary: fastly-sigsci-edge-mcp

> **Direct Synopsis:** This repository implements a Model Context Protocol (MCP) server for Fastly Signal Sciences. It lets AI agents easily synchronize, query, and map advanced security rules and event contexts.

## What Core Problem Does This Solve?
Security teams often struggle to parse vast amounts of WAF data during active incidents, slowing down threat containment and resolution.
* **Key Benefit 1:** Connects security state layers directly to AI agents using standard MCP protocols.
* **Key Benefit 2:** Speeds up incident response by allowing AI assistants to query and update security rules in real time.

## What is the Architecture and Tech Stack?
| Component | Technology | Role in Demo |
| :--- | :--- | :--- |
| Protocol Link | MCP Interface | Provides structured data schemas designed for AI ingestion |
| Security Provider | Signal Sciences Engine | Supplies underlying WAF rule configurations and real-time alert logs |

## How is This Solution Configured and Executed?
1. **Status:** Completed by Sai Kiao.
2. **Repository:** `https://github.com/fastly/fastly-sigsci-edge-mcp/`

## What Are the Primary Sales Engineering Use Cases?
* **AI-Driven SecOps Demos:** Shows modern security operation centers (SOCs) how AI agents can automate threat monitoring and mitigation.
* **Next-Gen WAF Workflows:** Highlights programmatic management options for Signal Sciences deployments.