{"id":46193475,"url":"https://github.com/log-wade/datacenter-mcp-server","last_synced_at":"2026-03-04T02:00:47.460Z","repository":{"id":340623029,"uuid":"1166866289","full_name":"log-wade/datacenter-mcp-server","owner":"log-wade","description":"Mission-critical data center engineering MCP server. 8 professional calculation tools for AI agents.","archived":false,"fork":false,"pushed_at":"2026-02-25T19:31:24.000Z","size":168,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-03-03T02:22:40.074Z","etag":null,"topics":["ai-agent","cooling","data-center","engineering","gpu","mcp","mcp-server","model-context-protocol","power","ups"],"latest_commit_sha":null,"homepage":"https://datacenter-mcp-server.vercel.app","language":"TypeScript","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/log-wade.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2026-02-25T17:36:54.000Z","updated_at":"2026-02-25T19:31:29.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/log-wade/datacenter-mcp-server","commit_stats":null,"previous_names":["log-wade/datacenter-mcp-server"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/log-wade/datacenter-mcp-server","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/log-wade%2Fdatacenter-mcp-server","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/log-wade%2Fdatacenter-mcp-server/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/log-wade%2Fdatacenter-mcp-server/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/log-wade%2Fdatacenter-mcp-server/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/log-wade","download_url":"https://codeload.github.com/log-wade/datacenter-mcp-server/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/log-wade%2Fdatacenter-mcp-server/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30069218,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-04T01:03:42.280Z","status":"online","status_checked_at":"2026-03-04T02:00:07.464Z","response_time":59,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai-agent","cooling","data-center","engineering","gpu","mcp","mcp-server","model-context-protocol","power","ups"],"created_at":"2026-03-03T01:47:43.318Z","updated_at":"2026-03-04T02:00:47.454Z","avatar_url":"https://github.com/log-wade.png","language":"TypeScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"# datacenter-mcp-server\n\nMission-critical data center engineering tools for AI agents. 8 professional-grade calculation engines covering cooling, power, GPU thermal optimization, UPS/battery sizing, tier classification, and commissioning workflows.\n\nBuilt on the [Model Context Protocol (MCP)](https://modelcontextprotocol.io) standard — works with Claude Desktop, Cursor, Windsurf, Cline, and any MCP-compatible client.\n\n## Quick Start\n\n### Claude Desktop\n\nAdd to your `claude_desktop_config.json`:\n\n```json\n{\n  \"mcpServers\": {\n    \"datacenter\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"datacenter-mcp-server\"]\n    }\n  }\n}\n```\n\n### Cursor / Windsurf\n\nAdd to your MCP settings:\n\n```json\n{\n  \"datacenter\": {\n    \"command\": \"npx\",\n    \"args\": [\"-y\", \"datacenter-mcp-server\"]\n  }\n}\n```\n\n### HTTP Mode (Remote)\n\n```bash\nTRANSPORT=http PORT=3001 API_KEY=your-secret npx datacenter-mcp-server\n```\n\n## Tools\n\n### dc_calculate_cooling_load\nCalculate ASHRAE-compliant cooling requirements for any data center facility. Inputs include IT load, redundancy level, climate zone, altitude, and humidity targets. Returns tonnage, airflow, chilled water capacity, and energy estimates.\n\n### dc_analyze_power_redundancy\nAnalyze electrical distribution from utility feed through UPS, PDU, and rack-level power. Supports N, N+1, 2N, and 2N+1 redundancy configurations with efficiency and cost analysis.\n\n### dc_assess_tier_classification\nEvaluate facility design against Uptime Institute Tier I-IV standards. Identifies compliance gaps and provides actionable upgrade recommendations.\n\n### dc_generate_commissioning_plan\nGenerate L1-L5 commissioning workflows with phase sequencing, test procedures, and documentation requirements per ASHRAE Guideline 0.\n\n### dc_analyze_rack_density\nAnalyze rack power density configurations from 5 kW to 100+ kW per rack. Covers cooling strategy selection, weight loading, and power distribution.\n\n### dc_gpu_cooling_optimizer\nOptimize cooling infrastructure for GPU/AI workloads (H100, A100, H200, B200, GB200). Calculates thermal loads, recommends cooling strategies (air, rear-door, direct liquid, immersion), sizes CDUs, and projects energy savings.\n\n### dc_ups_battery_sizing\nSize UPS modules and battery systems with N/N+1/2N/2N+1 redundancy. Compares VRLA vs lithium-ion with 10-year TCO analysis, floor space estimates, and weight calculations.\n\n### dc_reference_lookup\nQuery ASHRAE standards, Uptime Institute tier requirements, and industry best practices for data center design and operations.\n\n## Engineering Standards\n\nAll calculations comply with:\n\n- ASHRAE TC 9.9 thermal guidelines\n- Uptime Institute Tier Standard topology\n- NFPA 70 / NEC electrical code\n- ASHRAE Guideline 0 commissioning\n\n## Development\n\n```bash\n# Install dependencies\nnpm install\n\n# Build\nnpm run build\n\n# Run tests (264 tests across 7 suites)\nnpm test\n\n# Start in stdio mode (MCP default)\nnpm start\n\n# Start in HTTP mode\nnpm run start:http\n\n# Inspect with MCP Inspector\nnpm run inspect\n```\n\n## Architecture\n\n```\nsrc/\n  index.ts          # MCP server entry point, tool registration\n  types.ts          # TypeScript interfaces for all tools\n  constants.ts      # Engineering constants and reference data\n  middleware.ts      # Express middleware (auth, rate limiting, CORS)\n  schemas/          # Zod validation schemas per tool\n  services/         # Calculation engines per tool\ntests/              # Jest test suites (264 tests)\n```\n\n## License\n\nMIT - NextGen Mission Critical\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flog-wade%2Fdatacenter-mcp-server","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flog-wade%2Fdatacenter-mcp-server","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flog-wade%2Fdatacenter-mcp-server/lists"}