by nhevers · MCP Server · ★ 50
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Save tokens. Cut inference costs. Route compute through MVM nodes on the cheapest available energy. What is mica? LLM inference is expensive. Running agents 24/7 burns tokens and energy. Mica fixes this by routing your compute-heavy tasks through MVM (Mica Virtual Machine) nodes — distributed across regions with the cheapest renewable energy on the planet. Instead of paying full price for cloud compute at $0.10+/kWh, MVM routes your workloads to nodes running on Nordic hydroelectric ($0.02/kWh), Icelandic geothermal ($0.01/kWh), and Canadian hydro ($0.04/kWh). Same results, 40% lower cost. Mica runs as an MCP server plugin for Claude Code. When your agent needs to run inference, batch processing, or long-running tasks, it routes through MVM instead of standard cloud — saving tokens and money automatically. Install Claude Code Plugin Then install: Setup Get an API key at mica.energy/app Set your key: Or paste your key in chat and the plugin will prompt you to set it via . Tools | To
| Stars | 50 |
| Forks | 3 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 76.1027416867308/100 |
| Last Updated | 2026-04-06 |
| Created | 2026-04-06 |
| Platforms | claude-code, mcp, node |
| Est. Tokens | ~12k |
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mica-plugin is Claude Code plugin - route compute through MVM nodes on cheap renewable energy. Save tokens, cut inference costs.. It is categorized as a MCP Server with 50 GitHub stars.
mica-plugin is primarily written in TypeScript. It covers topics such as ai, claude-code, claude-plugin.
You can find installation instructions and usage details in the mica-plugin GitHub repository at github.com/nhevers/mica-plugin. The project has 50 stars and 3 forks, indicating an active community.
mica-plugin is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to mica-plugin on Agent Skills Hub include orchestkit, claude-historian-mcp, deterministic-agent-control-protocol. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.