"Information about OPNsense firewall and routing platform" matching MCP servers:

Routes subagent tasks across Claude and OpenAI lanes by task kind and quota state, deciding whether to spawn a single model, run a duel of both vendors, or run both and ship the merge. It records duels with attested proof-of-run session ids, grades sides blind with one judge per vendor, and tracks per-kind standings and lane pacing.

Aggregator MCP proxy that collapses N downstream MCP servers into 4 meta-tools with progressive tool discovery, and compresses large tool outputs (HTML→Markdown, JSON summarization) with full-output retrieval via read_more and a per-session token-savings report.

A secure MCP server for managing OPNsense firewalls through AI assistants. Provides 81 tools across system, firewall, network, DNS, DHCP, VPN, HAProxy, services, diagnostics, and security domains.

An MCP routing proxy that prevents LLMs from executing unintended tools. It securely curates, filters, and routes tools from multiple backend MCP servers. (LLMが意図しないツールを実行するのを防ぐMCPルーティングプロキシ。複数のバックエンドMCPサーバーからのツールを安全にキュレーション、フィルタリング、ルーティングします。)

A local MCP server that acts as a policy-based firewall for personal context, letting users control agent access to their data with deny-by-default rules, per-field grants, and an audit trail.

A policy and audit layer for Model Context Protocol (MCP). MCP Firewall sits transparently between any MCP client (Claude Desktop, Cursor, VS Code, etc.) and an upstream MCP server, allowing you to inspect, allow, block, or audit requests before they reach the server.

Sits in front of any MCP server to enforce allow/ask/block policies on tool calls, paths, shell commands, and network domains, with local approval prompts and an audit log.

A policy-based security layer for AI agents and MCP tools that evaluates tool requests against security policies before allowing, denying, or requiring human approval for execution.

Enables AI coding agents to analyze git diffs for behavior-aware change reports, map downstream blast radius, and enforce deterministic risk gates through the Model Context Protocol.

A multi-agent AI security layer that protects LLMs from prompt injection, jailbreaks, and policy violations via MCP tools.

Enables AI agents to securely invoke tools by enforcing identity proof, capability verification, and risk scoring on every request, blocking unsafe calls before they execute.

Routes tasks to the appropriate model across cloud, on-device, and org-hosted endpoints based on sensitivity, role, and difficulty, with provable egress control to keep sensitive content within trust boundaries.

MCP server for Argo CD and Vault that allows authenticated users to run CLI commands via GitLab SSO, with confirmation for dangerous operations and secret redaction from model context.

Read-only MCP server that exposes Kubernetes platform state (tenants, pods, SLOs, ArgoCD applications, chaos schedules, and catalog services) to AI agents, enabling natural language queries about cluster health and configuration.

Analyzes codebases for cross-platform compatibility issues, detecting platform-specific APIs, file path problems, line ending inconsistencies, and shell command incompatibilities across Windows, macOS, and Linux.

MCP server for operating and testing Android devices with AI agents. Provides observation and action tools for interactive control and spreadsheet-driven test runs.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

MCP server wrapping a mock internal ops platform (FastAPI + SQLite) so Claude Code can read and write employee, project, task, and time data through natural language.

Enables AI agents to interact with ServiceNow through MCP, providing schema inspection, record CRUD, attachments, audit, Flow Designer, and platform investigations with policy-guarded access.

A proxy MCP server that bridges AI assistants to a remote Eulerian Marketing Platform, handling authentication and request forwarding for querying Eulerian API endpoints.