이 저장소는 Meraki 네트워크에서 두 MCP 서버를 사용하여 에이전트 워크플로우를 구축하는 방법을 설명합니다. 시스템은 다음과 같습니다.

• A **Splunk MCP Agent ** 네트워크 변경을 감지합니다. *Splunk MCP Server에 대한 William Searle에 적용됩니다. *
• Meraki MCP Agent**를 역동적으로 변경합니다.

Agentic AI는 자연적인 언어에 근거를 둔 탐지와 재약을 취급합니다 - 요구되는 hardcoded 관현 없음.

---

♨ 어떻게 작동

1. 당신은 물었다 : "내 Meraki 네트워크에서 무슨 변경?
2. Splunk MCP Agent queries Splunk는 SDK를 사용하여 설정 드리프트를 반환합니다.
3. ** Meraki MCP Agent**는 진실의 근원에 변화를 비교하고 적절한 Meraki API를 반대합니다.

---

542️ 예약

• Python 3.10 이상
• 액세스 :
• 관련 로그가있는 Splunk 인스턴스
• Meraki Dashboard API 키
• Claude 데스크탑 또는 MCP 호환 클라이언트
• claude_desktop_config.json] 올바른 도구 등록 및 MCP 서버 경로로 구성

---

☸ 임명

** 저장소:**

Splunk MCP Setup (로컬 설치)

더 많은 Splunk MCP 설치 옵션 체크 아웃 : https://github.

🧠 Self-Healing Network with MCP Agents

This repository demonstrates how to build agentic workflows using two MCP servers to detect and reverse configuration drift in a Meraki network. The system utilizes:

• A Splunk MCP Agent to detect network changes. Credit to William Searle for the Splunk MCP Server.
• A Meraki MCP Agent to reverse unauthorized changes.

Agentic AI handles both detection and remediation based on natural language prompts—no hardcoded orchestration required.

---

🚀 How It Works

1. You ask: “What changed in my Meraki network?”
2. The Splunk MCP Agent queries Splunk using its SDK and returns configuration drift.
3. The Meraki MCP Agent compares the change to the source of truth and calls the appropriate Meraki API to reverse it.

---

🛠️ Prerequisites

• Python 3.10 or higher
• Access to:
  • A Splunk instance with relevant logs
  • A Meraki Dashboard API key
  • Claude Desktop or any MCP-compatible client
• claude_desktop_config.json configured with correct tool registration and MCP server paths

---

📦 Installation

Clone the repository:

git clone https://github.com/kiskander/mcp-splunk-meraki.git
cd mcp-splunk-meraki

Splunk MCP Setup (Local Installation)

for more Splunk MCP installation options checkout: https://github.com/livehybrid/splunk-mcp

1. Access Splunk MCP:

   cd mcp-splunk-meraki/SplunkMCP
   

2. Install dependencies using Poetry:

   poetry install
   

3. Configure environment variables:

   Copy the example environment file and update it with your Splunk credentials:

   cp .env.example .env
   

   Update the .env file with the following:

   SPLUNK_HOST=your_splunk_host
   SPLUNK_PORT=8089
   SPLUNK_USERNAME=your_username
   SPLUNK_PASSWORD=your_password
   SPLUNK_SCHEME=https
   VERIFY_SSL=true
   FASTMCP_LOG_LEVEL=INFO
   SERVER_MODE=stdio
   

4. Run the Splunk MCP:

   poetry run python splunk_mcp.py stdio
   

---

Meraki MCP Setup

1. Install uv (if not already installed):

   For macOS/Linux:

   brew install uv
   

2. Set Up Your Meraki MCP Project:

   cd mcp-splunk-meraki/MerakiMCP
   

3. Install dependencies using uv:

   uv init
   
   uv venv
   source .venv/bin/activate # or .venv\Scripts\activate on Windows
   
   uv add "mcp[cli]"
   uv add "meraki"  
   

4. Run the Meraki MCP Agent:

   python meraki_mcp.py
   

---