Add Rarefied Earth Groundwork company-state MCP

Co-authored-by: Cursor <cursoragent@cursor.com>

README.md

@@ -2186,6 +2186,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
 - [pfillion42/memviz](https://github.com/pfillion42/memviz) 📇 🏠 🍎 🪟 🐧 - Visual explorer for [MCP Memory Service](https://github.com/doobidoo/mcp-memory-service) SQLite-vec databases. Browse, search, filter, edit memories with dashboard, timeline, UMAP projection, semantic clustering, duplicate detection, and association graph.
 - [pinecone-io/assistant-mcp](https://github.com/pinecone-io/assistant-mcp) 🎖️ 🦀 ☁️ - Connects to your Pinecone Assistant and gives the agent context from its knowledge engine.
 - [pomazanbohdan/memory-mcp-1file](https://github.com/pomazanbohdan/memory-mcp-1file) 🦀 🏠 🍎 🪟 🐧 - A self-contained Memory server with single-binary architecture (embedded DB & models, no dependencies). Provides persistent semantic and graph-based memory for AI agents.
+- [Rarefied-Earth/groundwork](https://github.com/Rarefied-Earth/groundwork) 📇 ☁️ - Hosted company-state MCP for operating SMBs (brand, voice, charter, priorities, entitled modules/skills). Anonymous public discovery at `https://connector.rarefied.earth/public/mcp` proves live value in under 10 seconds; tenant feed after trial. Official registry: `io.github.Rarefied-Earth/groundwork`. [Product](https://rarefied.earth/groundwork/)
 - [ragieai/mcp-server](https://github.com/ragieai/ragie-mcp-server) 📇 ☁️ - Retrieve context from your [Ragie](https://www.ragie.ai) (RAG) knowledge base connected to integrations like Google Drive, Notion, JIRA and more.
 - [ravi-labs/mindmap-mcp-server](https://github.com/ravi-labs/mindmap-mcp-server) [![ravi-labs/mindmap-mcp-server MCP server](https://glama.ai/mcp/servers/ravi-labs/mindmap-mcp-server/badges/score.svg)](https://glama.ai/mcp/servers/ravi-labs/mindmap-mcp-server) 📇 🏠 - Local-first memory & context-handoff across AI tools — capture context in one tool, resume it in another, with graceful decay, a persona layer, and a portable memory passport.
 - [remembra-ai/remembra](https://github.com/remembra-ai/remembra) [![remembra MCP server](https://glama.ai/mcp/servers/remembra-ai/remembra/badges/score.svg)](https://glama.ai/mcp/servers/remembra-ai/remembra) 🐍 📇 🏠 ☁️ 🍎 🪟 🐧 - Persistent memory layer for AI agents with entity resolution, PII detection, AES-256-GCM encryption at rest, and hybrid search. 100% on LoCoMo benchmark. Self-hosted.