"How to Create 2D Fighting Games in Godot Engine" matching MCP servers:

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

Enables programming agents to capture errors and conversation signals, reflect on root causes, consolidate reusable skills, and retrieve relevant context for future tasks, providing a self-learning memory loop.

Persistent memory for AI agents with semantic memory, belief tracking, and dream consolidation, enabling cross-session knowledge retention.

Local-first stdio MCP server for agent relationship-continuity state: PAD mood, affective pulse, trust, decay, and boundary signals kept beside factual memory.

MCP server for querying a personal knowledge base using semantic RAG, powered by DeepSeek and local embeddings from Ollama.

A persistent world your agents share across sessions and models. MCP memory server with semantic memory retrieval, cross-agent handoff, a hosted remote endpoint with OAuth, a free 24-hour room, and an open-source local stdio server.

A local MCP server that gives AI assistants a long-term memory by capturing sessions verbatim and surfacing relevant context automatically.

Provides coding agents with persistent, evidence-backed project memory and knowledge across sessions, using a structured memory tree and local knowledge base.

A local-first, agent-agnostic MCP server that provides semantic search, persistent memory, and automated code review capabilities for development workflows. It leverages the Auggie SDK to offer advanced tools for codebase indexing, implementation planning, and deterministic static analysis.

An MCP server that structures AI reasoning as directed acyclic graphs of semantic thoughts, enabling explicit dependencies, assumption tracking, and cascade invalidation for transparent decision-making.

A narrative graph engine that enables LLMs to generate, track, and mutate complex fictional worlds while maintaining consistency between factions, characters, and locations. It acts as a specialized RAG framework for storytelling, allowing models to manage thousands of entities without exceeding context limits.

Surfaces forgotten notes from markdown vaults using wikilink graph structure and file mtime to identify dormant notes, then generates cross-domain bridge queries for serendipitous rediscovery.

A graph database MCP server that lets AI assistants build, analyze, and visualize relationship graphs with algorithms like PageRank and cycle detection.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

A read-only Model Context Protocol server that exposes a semantic knowledge base to AI agents via 27 tools. It enables querying of documents and data integrated from sources like Notion, SharePoint, HubSpot, and Slack.

Surface forgotten notes from markdown vaults using DMN-inspired replay cycle to identify dormant notes and generate cross-domain connections.

Enables AI assistants to have a living memory with atomic knowledge storage, multi-factor recall, organic decay, automatic learning, and graph traversal via MCP.

An MCP server that provides persistent memory for AI agents by storing session snapshots, factual memories, and conversation summaries. It enables seamless continuity between interactions by allowing agents to restore previous emotional states and recall relevant past experiences.

A multi-tenant memory and reasoning substrate for AI agents that provides tenant-isolated, append-only, and auditable memory with vertical business engines for procurement, sales, project management, and more, exposed via MCP and REST.

Turn Obsidian notes into agent-ready context, preview-only plans, and safe repo handoffs.