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coreyhines/opnsense-mcp

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coreyhines/opnsense-mcp — indexed from awesome-mcp-servers-punkpeye

C

MCP

coreyhines/opnsense-mcp

Added 1 June 2026

Overview

A Model Context Protocol server for OPNsense, the open-source firewall platform. It enables AI assistants to interact with OPNsense through standardized MCP queries. Built in Python, it provides an interface for programmatic control of OPNsense features.

Best for

Best for
Developers automating OPNsense firewall management through AI interfaces

Use cases

  • Managing firewall rules via natural language commands
  • Monitoring network traffic and security events
  • Automating OPNsense configuration tasks

How to use

Install

uv pip install -r requirements.txt

Tested with

Claude Code, Cursor, Continue

Example client config

{\n  "mcpServers": {\n    "opnsense-mcp": {\n      "command": "/bin/bash",\n      "args": ["/absolute/path/to/opnsense-mcp/mcp_start.sh"],\n      "cwd": "/absolute/path/to/opnsense-mcp"\n    }\n  }\n}

Notes

A Model Context Protocol server for OPNsense, the open-source firewall platform. It enables AI assistants to interact with OPNsense through standardized MCP queries. Built in Python, it provides an interface for programmatic control of OPNsense features.

4 stars on GitHub. Last updated 2026-05-16. Licensed MIT.

Use cases

  • Managing firewall rules via natural language commands
  • Monitoring network traffic and security events
  • Automating OPNsense configuration tasks

Pros

  • Bridges AI assistants with OPNsense for automation
  • Straightforward Python implementation with MCP standard
  • Open source and extensible

Cons

  • Low star count suggests limited adoption or early stage
  • Requires OPNsense instance and MCP-compatible client
  • Documentation and community support may be sparse

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Bridges AI assistants with OPNsense for automation
  • Straightforward Python implementation with MCP standard
  • Open source and extensible

Cons

  • Low star count suggests limited adoption or early stage
  • Requires OPNsense instance and MCP-compatible client
  • Documentation and community support may be sparse
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