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    Lets Claude analyse your Octopus Energy account: usage, costs, tariff comparisons, Saving Sessions, Octoplus rewards.
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    Unified deployment dashboard MCP server for AI agents. 9 tools to manage services across Vercel, Render, Railway, and Fly.io — deploy status, logs, service listing, environment variables, rollback, and health checks from one endpoint. Free tier: 50 requests/IP/day.
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    MIT
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    AI-powered VMware vCenter/ESXi monitoring and operations. 20 MCP tools for inventory queries, health monitoring, VM lifecycle management, fast provisioning (Linked Clone, OVA, template deploy), snapshot management, and datastore browsing. Supports vSphere 6.5–8.0. Works with local models via Ollama/LM Studio.
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    An MCP server that gives AI agents deterministic, verified access to ISO 8583 field specs, MTI decoding, jPOS packager XML generation, deploy descriptor validation, message building, and jPOS documentation search.
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    VibOps MCP is the control plane between your AI agents and your GPU infrastructure. 74 tools covering: GPU fleet management (deploy, scale, monitor across NVIDIA, AMD, Intel, AWS, Google, Groq), Agent Infrastructure Control Plane (per-agent GPU cost, budget enforcement, model policies, dependency graph), governance (AI Act, SOC 2, immutable HMAC audit chain), and GPU FinOps (chargeback, waste..)..
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    A production-ready MCP server template that enables developers to quickly build and deploy MCP servers with dynamic tool/resource loading, YAML-based prompts, and seamless OpenShift deployment. Supports both local development with hot-reload and production HTTP deployment with optional JWT authentication.
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    A Python-based MCP server implementation that can be easily installed via pip or directly from GitHub, providing a simple way to deploy and run MCP server functionality.
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