From 8408b211f6df3247af1e469b93c4b03ea59f3889 Mon Sep 17 00:00:00 2001 From: Matt Joyce Date: Thu, 2 Oct 2025 11:14:29 +1000 Subject: [PATCH] Add mcp-construe and mcp-persona-sessions to Knowledge & Memory Two Python MCP servers for knowledge management and professional development: - mcp-construe: Obsidian vault context management with frontmatter filtering - mcp-persona-sessions: Structured AI sessions for interview prep and coaching Both local servers actively maintained and production-tested. --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index dc560328..222e7a3e 100644 --- a/README.md +++ b/README.md @@ -786,10 +786,12 @@ Persistent memory storage using knowledge graph structures. Enables AI models to - [jinzcdev/markmap-mcp-server](https://github.com/jinzcdev/markmap-mcp-server) 📇 🏠 - An MCP server built on [markmap](https://github.com/markmap/markmap) that converts **Markdown** to interactive **mind maps**. Supports multi-format exports (PNG/JPG/SVG), live browser preview, one-click Markdown copy, and dynamic visualization features. - [kaliaboi/mcp-zotero](https://github.com/kaliaboi/mcp-zotero) 📇 ☁️ - A connector for LLMs to work with collections and sources on your Zotero Cloud - [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 +- [mattjoyce/mcp-construe](https://github.com/mattjoyce/mcp-construe) 🐍 🏠 - FastMCP server for intelligent Obsidian vault context management with frontmatter filtering, automatic chunking (95k chars), and secure bidirectional knowledge operations. Curate personal knowledge for AI conversations. - [modelcontextprotocol/server-memory](https://github.com/modelcontextprotocol/servers/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. - [pi22by7/In-Memoria](https://github.com/pi22by7/In-Memoria) 📇 🦀 🏠 🍎 🐧 🪟 - Persistent intelligence infrastructure for agentic development that gives AI coding assistants cumulative memory and pattern learning. Hybrid TypeScript/Rust implementation with local-first storage using SQLite + SurrealDB for semantic analysis and incremental codebase understanding. - [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. +- [mattjoyce/mcp-persona-sessions](https://github.com/mattjoyce/mcp-persona-sessions) 🐍 🏠 - Enable AI assistants to conduct structured, persona-driven sessions including interview preparation, personal reflection, and coaching conversations. Built-in timer management and performance evaluation tools. - [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. - [TechDocsStudio/biel-mcp](https://github.com/TechDocsStudio/biel-mcp) 📇 ☁️ - Let AI tools like Cursor, VS Code, or Claude Desktop answer questions using your product docs. Biel.ai provides the RAG system and MCP server. - [topoteretes/cognee](https://github.com/topoteretes/cognee/tree/dev/cognee-mcp) 📇 🏠 - Memory manager for AI apps and Agents using various graph and vector stores and allowing ingestion from 30+ data sources