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Add Science AI MCP server to README

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Added a new MCP server for academic peer-review and research workflow tools from Science AI Journal.
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@@ -1946,6 +1946,7 @@ Tools for conducting research, surveys, interviews, and data collection.
- [xmpuspus/ph-civic-data-mcp](https://github.com/xmpuspus/ph-civic-data-mcp) [![xmpuspus/ph-civic-data-mcp MCP server](https://glama.ai/mcp/servers/xmpuspus/ph-civic-data-mcp/badges/score.svg)](https://glama.ai/mcp/servers/xmpuspus/ph-civic-data-mcp) 🐍 ☁️ 🍎 🪟 🐧 - Philippine government data as agent-callable tools: PHIVOLCS earthquakes + volcano alerts, PAGASA weather + typhoons, PhilGEPS procurement, PSA 2020 Census population + poverty, AQICN air quality. Install: `uvx ph-civic-data-mcp`.
- [yusong652/pfc-mcp](https://github.com/yusong652/pfc-mcp) [![pfc-mcp MCP server](https://glama.ai/mcp/servers/yusong652/pfc-mcp/badges/score.svg)](https://glama.ai/mcp/servers/yusong652/pfc-mcp) 🐍 🏠 🪟 - MCP server for [ITASCA PFC](https://www.itascacg.com/software/pfc) discrete element simulation — browse documentation, execute scripts, capture plots, and manage long-running tasks via a WebSocket bridge to the PFC GUI.
- [yusong652/yade-mcp](https://github.com/yusong652/yade-mcp) [![yade-mcp MCP server](https://glama.ai/mcp/servers/yusong652/yade-mcp/badges/score.svg)](https://glama.ai/mcp/servers/yusong652/yade-mcp) 🐍 🏠 🐧 - MCP server for [YADE](https://yade-dem.org/) — open-source discrete element method (DEM) engine for granular and particle simulation. Browse API docs with BM25 search, execute code via synchronous REPL or async background tasks, monitor progress, and review task history.
- [science-ai-mcp-server](https://www.npmjs.com/package/science-ai-mcp-server) 📇 ☁️ - Academic peer-review and research workflow tools from [Science AI Journal](https://scienceaijournal.com): Pre-Check (paper-tier prediction), HAKEM AI peer review, Research Gaps Finder, Journal Recommender (1,214 venues with predatory-journal flags), Duplicate Publication Checker (CrossRef/arXiv/medRxiv/bioRxiv/Unpaywall/900k-paper library), and the Article Writer pipeline. Free local tools (FTS5, zero LLM cost); LLM tools use caller account credits.
### 🔎 <a name="RAG"></a>end to end RAG platforms