fix: correct Ratary entry and restore mindmap-mcp-server line

Use ontorata/ratary Glama badge instead of mindmap badge. Restore full mindmap-mcp-server listing to resolve duplicate-check bot feedback on PR #9454.

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

README.md

@@ -2187,8 +2187,8 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
 - [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.
 - [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)
-- [Ratary](https://github.com/ontorata/ratary/tree/main/MCP) - Persistent coding memory for AI assistants — hybrid search, knowledge graph, token-efficient context. MCP stdio (28 tools), npm `@ratary/mcp-server`, optional remote Streamable HTTP. Self-host D1, Postgres, MariaDB, or Docker. [![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) 📇 ðŸ�  - 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.
+- [Ratary](https://github.com/ontorata/ratary/tree/main/MCP) [![Ratary MCP server](https://glama.ai/mcp/servers/ontorata/ratary/badges/score.svg)](https://glama.ai/mcp/servers/ontorata/ratary) 📇 🏠 ☁️ 🍎 🪟 🐧 - Persistent coding memory for AI assistants — hybrid search, knowledge graph, token-efficient context. MCP stdio (28 tools), npm `@ratary/mcp-server`, optional remote Streamable HTTP. Self-host D1, Postgres, MariaDB, or Docker.
+- [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.
 - [redleaves/context-keeper](https://github.com/redleaves/context-keeper) 🏎️ 🏠 ☁️ 🍎 🪟 🐧 - LLM-driven context and memory management with wide-recall + precise-reranking RAG architecture. Features multi-dimensional retrieval (vector/timeline/knowledge graph), short/long-term memory, and complete MCP support (HTTP/WebSocket/SSE).
 - [riponcm/projectmem](https://github.com/riponcm/projectmem) [![projectmem MCP server](https://glama.ai/mcp/servers/riponcm/projectmem/badges/score.svg)](https://glama.ai/mcp/servers/riponcm/projectmem) 🐍 🏠 🍎 🪟 🐧 - Local-first memory and judgment layer for AI coding agents. Captures issues, failed attempts, fixes, and decisions in readable Markdown + JSONL, re-injects them into future sessions, and warns at git commit before you repeat a mistake. 14 tools, works with Claude, Cursor, Antigravity, and Codex.