"How to create a game using Unity" matching MCP servers:

The first Model Context Protocol server for Unity projects. It gives AI assistants real understanding of Unity scenes, prefabs, and C# scripts through a queryable knowledge graph.

A self-hostable, open-source, semantically-searchable Agent Skills registry delivered over MCP, with a three-tier progressive disclosure architecture.

Author rules from policy docs, then decide: a Rete engine gives the verdict, an LLM explains why.

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

Provides a hybrid memory architecture with a thin SQLite index and Markdown cold storage, enabling AI agents to write, query, link, and rebuild long-term memories via MCP tools, model-agnostic and zero third-party dependencies.

Enables AI agents to query a local knowledge graph built from document collections using hybrid search (BM25 + vector fusion) and entity-relationship extraction. Supports privacy-first, offline operation with tools for semantic search, entity graph exploration, and corpus statistics.

MCP server for a personal notes/knowledge base that enables AI assistants to create, search, and retrieve notes using natural language. It exposes tools like create_note and search_notes, resources for each note, and a summarize_tag prompt.

Provides a compressed knowledge graph of the NVIDIA AI developer stack for deterministic traversal, enabling agents to answer questions about dependencies and prerequisites with minimal tokens.

Extends large language model context length up to 60 times using gravitational memory, designed for Claude Code and Anthropic AI models.

A server that provides data retrieval capabilities powered by Chroma embedding database, enabling AI models to create collections over generated data and user inputs, and retrieve that data using vector search, full text search, and metadata filtering.

Extends LLM context windows by 15-60× using gravitational memory compression, enabling massive context extension for codebases, research papers, and long documents.

Provides a shared, persistent memory layer for AI assistants, letting them read and write to a local Obsidian vault through MCP with validation, secret rejection, and deduplication.

Gives an AI game master a persistent memory for tabletop roleplaying games by storing worlds, characters, plots, and scenes. It enables saving, searching, and loading game state (via MCP tools) so the GM doesn't have to recall plot and details only from the context window.

A multimodal local memory MCP server that lets AI agents search across text, PDFs, images, audio, and video using Gemini Embedding 2 and a local ChromaDB.

Provides a compiled knowledge substrate, extracting atomic claims from an append-only capture log and querying a bitemporal claim graph over MCP. Read-only by default, with opt-in writes for trusted sources.

An MCP server for managing work logs, research results, and task checkpoints to enable seamless collaboration and state recovery between AI agents. It provides a persistent memory layer for tracking project history and resuming workflows across different sessions or tools.

Provides LLM access to Workflowy's API, enabling agents to create, read, update, delete, and reorganize nodes in a Workflowy outline.

Enables AI assistants to read, create, search, update, and delete Apple Notes through natural language conversation, using JXA to communicate directly with the Notes app.

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

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.