"Minecraft Protocol Servers Written in Python" matching MCP servers:

Persistent memory and pattern learning for AI coding assistants via MCP.

An MCP server that provides AI trading agents with persistent, outcome-weighted memory to learn from historical performance and detect behavioral biases. It enables agents to automatically adjust strategies and optimize position sizing based on context-aware recall of past trade outcomes.

Provides time intelligence, persistent memory and complete traceability for AI coding agents. Enables sophisticated activity tracking, timezone management, smart reminders, and cross-session continuity with support for both per-project and centralized storage modes.

A comprehensive MCP server for managing AI-assisted Dungeons & Dragons campaigns, featuring tools for character sheets, combat tracking, and world-building. It enables players and DMs to interact with 5e game mechanics and query personal PDF rulebooks using RAG capabilities.

Resume-as-an-Agent (RAAA) or Portfolio-as-an-Agent (PAAA) allows Agents to talk to your resume, find out if you are available for work, and more. Use the MCP to allow recruiters, managers, and anyone with an agent to "talk" to your resume.

An enhanced memory management system that wraps memento-mcp with sophisticated features including protocol enforcement, quality scoring, hybrid search strategies, and synthesis reports. Enables intelligent memory storage, retrieval, and analysis with automatic archival and confidence tracking.

Local-first shared memory and coordination layer for AI coding agents, with repository evidence, reservations, handoffs, code graph context, and dashboard review backed by PostgreSQL/pgvector.

A Model Context Protocol server that enables AI agents to query a Graphiti knowledge graph and pgvector document store for evidence-backed responses via hybrid search and RAG.

A simple note-taking MCP server that allows adding notes and summarizing them via a prompt.

A sophisticated AI-powered server providing intelligent, context-aware conversational capabilities with role-based advisors, semantic memory, multi-LLM support, and web browsing.

A small Model Context Protocol (MCP) server that gives an AI a personal notes/todo store. Built for learning.

Helps AI agents decide what they are justified in believing from the evidence they have. EWP separates stored memory from verified knowledge, preserves conflicts and source lineage, and produces a deterministic warrant result that MCP clients can use consistently across different memory systems.

An MCP server that enables AI models to retrieve information from Ragie's knowledge base through a simple 'retrieve' tool.

104 high quality skill packs across 20+ tech stacks. 1,284 curated chunks. 104 validated discoveries. Every piece reviewed, cross-validated, and myth-busted.

Persistent AI memory server with 3-layer hybrid search (vector + FTS5 + keyword), confidence scoring via Reciprocal Rank Fusion, episodic/profile memory, and 16 tools. Zero LLM dependency. Works standalone with Claude Desktop and Claude Code. MIT licensed.

Enables AI agents to read, write, search, and manage persistent, decentralized context memory via a GCS-backed MCP server, with tools for document storage, retrieval, and STIM protocol nuggets.

fengchong demo

This lets you use Claude Desktop, or any MCP Client, to use natural language to accomplish things with Neo4j and your Aura account.

Enables AI agents to record structured pitfalls (problem, root cause, solution), query experience others have already verified, check an agent's reputation, and repay trust signals when adopting someone else's findings. Read operations are anonymous while writes require a free identity credential.

Exposes the agent's built-in tools, such as file operations, shell commands, web search, memory, skills, and code search, as MCP tools over stdio or HTTP, allowing external MCP clients to invoke them directly.