From fcfeca2be38950ff2a5ee5b4f3dbe6c9bc8147cb Mon Sep 17 00:00:00 2001 From: Barada Sahu Date: Sun, 11 Jan 2026 18:42:39 +0530 Subject: [PATCH] Add mercurialsolo/counsel-mcp server --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index a2a67957..7e248f0a 100644 --- a/README.md +++ b/README.md @@ -925,6 +925,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to - [pallaprolus/mendeley-mcp](https://github.com/pallaprolus/mendeley-mcp) 🐍 ☁️ - MCP server for Mendeley reference manager. Search your library, browse folders, get document metadata, search the global catalog, and add papers to your collection. - [louis030195/easy-obsidian-mcp](https://github.com/louis030195/easy-obsidian-mcp) 📇 🏠 🍎 🪟 🐧 - Interact with Obsidian vaults for knowledge management. Create, read, update, and search notes. Works with local Obsidian vaults using filesystem access. - [mem0ai/mem0-mcp](https://github.com/mem0ai/mem0-mcp) 🐍 🏠 - A Model Context Protocol server for Mem0 that helps manage coding preferences and patterns, providing tools for storing, retrieving and semantically handling code implementations, best practices and technical documentation in IDEs like Cursor and Windsurf +- [mercurialsolo/counsel-mcp](https://github.com/mercurialsolo/counsel-mcp) 📇 ☁️ 🏠 🍎 🪟 🐧 - Connect AI agents to the Counsel API for strategic reasoning, multi-perspective debate analysis, and interactive advisory sessions. - [modelcontextprotocol/server-memory](https://github.com/modelcontextprotocol/servers-archived/tree/main/src/memory) 📇 🏠 - Knowledge graph-based persistent memory system for maintaining context - [MWGMorningwood/Central-Memory-MCP](https://github.com/MWGMorningwood/Central-Memory-MCP) 📇 ☁️ - An Azure PaaS-hostable MCP server that provides a workspace-grounded knowledge graph for multiple developers using Azure Functions MCP triggers and Table storage. - [nonatofabio/local-faiss-mcp](https://github.com/nonatofabio/local_faiss_mcp) 🐍 🏠 🍎 🐧 - Local FAISS vector database for RAG with document ingestion (PDF/TXT/MD/DOCX), semantic search, re-ranking, and CLI tools for indexing and querying