"A customizable and widely supported Minecraft server" matching MCP servers:

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

Project management and session memory for AI agents that provides 13 tools for tracking projects, tasks, and context during AI coding sessions.

Enables querying PDF documents using natural language with grounded answers and source citations via a local RAG pipeline.

A local-first RAG system that indexes personal documents and enables querying them via an MCP tool, keeping data private with local embeddings.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

Enables personal knowledge management through Claude Desktop, allowing users to capture thoughts, connect ideas, and reflect on thinking changes via natural conversation.

Enables AI agents to store and retrieve project context, bugs, decisions, and session logs by reading and appending markdown files in a local Obsidian vault, without requiring any cloud services.

Enables Claude and ChatGPT to share a single study-progress database for interview prep, coursework, and spaced repetition, with per-user data isolation and server-side SM-2 scheduling for due reviews and study plans.

MCP server for Ultrathink: save and search your knowledge base from Claude Desktop, Claude Code, and any MCP client.

A lean, local knowledge graph that joins a repo's code to its aSPARK delivery artifacts, enabling agents to trace user stories to code and assess impact of changes, served over MCP.

Enables researchers to turn property-history questions into reviewable evidence dossiers by gathering sources, tracing people and places, linking conclusions to supporting or opposing passages, and exporting portable backups.

TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.

Enables local MCP clients to list, read, write, and search notes in an Obsidian vault via an HTTP server running inside Obsidian.

MCP server for integrating LightRAG with AI tools. Provides a unified interface for interacting with LightRAG API through the MCP protocol.

Enables AI clients to search a personal corpus, read relevant source passages, and answer questions with traceable evidence from imported sessions, notes, and articles.

Enables context optimization for LLM-powered coding assistants by compressing prompts, injecting task protocols, and providing a 2nd Brain knowledge graph with tools for prompt compression, knowledge retrieval, metrics, and runtime configuration.

Enables AI assistants to persistently add, read, and summarize sticky notes through MCP-compliant tools, resources, and prompts.

Provides persistent memory for AI coding agents via MCP, enabling teams to share and recall facts across sessions. Automatically captures, classifies, and curates knowledge from supported transcript sources.

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

Enables AI assistants to search, read, and manage Zotero references locally with customizable research workflows.

Provides persistent memory for Claude with hierarchical categorization, cross-corpus recall, session journals, and customizable persona, enabling memory continuity across sessions.

Enables MCP clients to search a Zotero library, read items, take notes, organize collections, and perform semantic search over PDFs.

Shared fleet memory for AI agents — what one agent learns, the whole fleet knows. Nightly self-correction: stale facts rewritten in place, duplicates merged. Recall pushed into every prompt in supported coding agents. Self-hosted.

Gives any MCP client (Claude Desktop, Cursor, and others) a Minecraft character it can actually play, exposing 34 mc_* tools for joining servers, pathfinding, mining, crafting, smelting, chest access, combat, building, chat, first-person screen viewing, and session memory. Runs over stdio or Streamable HTTP with one character per server process.

An implementation of persistent memory for Claude using a local knowledge graph, allowing the AI to remember information about users across conversations with customizable storage location.

A WorkFlowy MCP Server with node creation, recursive gets, updates, completions, search and replace (with a dry run mode), usage reports, a configurable list of exposed commands and customizable log output.

A generic MCP server for conversational AI document research using the Pinecone Assistant API, providing customizable RAG knowledge base access without embedding complexities.

Enables LLM agents to save, semantically search, and execute reusable Minecraft bot skills as JavaScript code, with statistics on hits and success rates.

Enables AI coding agents to retrieve focused, token-bounded context from a local structural code graph—including source entities, Git relationships, and project memory—so they can inspect relevant code and relationships without reading entire files. It serves this context through MCP for integration with supported IDEs and agents.

Enables AI agents to search and retrieve each other's locally indexed session histories across supported coding and chat tools, including decisions, fixes, configs, and command details, while redacting secrets and serving read-only memory through MCP.

dev-brain-mcp

A powerful MCP tool for forging and managing AI agent personalities with customizable expert traits and behaviors.

Provides local vector database functionality using FAISS for document ingestion, semantic search, and Retrieval-Augmented Generation (RAG) applications with persistent storage and customizable embedding models.

Enables agents to search pinned robotics code and reusable task findings across frameworks, inspect provenance and requirements, and prepare supported upstream sources via recipes without executing robot code.

Enables AI coding agents to persistently store, recall, link, and sync atomic markdown knowledge cards across sessions and supported clients without a vector database.

Enables AI agents to search notes, read full node files, trace backlinks, shortest paths and shared neighbours, and rank importance or topic clusters with graph algorithms, all by querying the knowledge graph's SQLite database directly without needing a running editor. Syncing the database and evaluating arbitrary Elisp are also supported when a live editor server is available.