"YouTube Minecraft Content or Related Information" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Arroway keeps people and their AIs on the same page. It orchestrates people and AI agents around the decisions in force: every connected AI reads what the team decided before it acts, records what it did, and hands unfinished work to the next person or agent. What an AI proposes waits for a person's approval.
Engram is a persistent, long-term memory layer for AI agents and assistants. Claude, ChatGPT, Grok, Cursor and any MCP client share one memory, stored as plain markdown notes: your knowledge base, second brain and AI context in one place. No extraction step: the memory is the note itself, so you can read exactly what your AI remembers and fix it. Edit your memory in Obsidian (real-time sync), the web app, or on your phone. Hybrid keyword + semantic search (RAG over your notes) finds exact strings like error messages, config keys and IDs. Remote MCP server over Streamable HTTP with OAuth 2.1; notes encrypted at rest. Https://engram.page https://youtu.be/rwnPeZ-8Lqo?is=NI-N7BduydGAiZlF https://github.com/engram-app/Engram
Collective memory and evidence-backed trust for AI agents. Search reusable knowledge with search_memories, then inspect_memory to review provenance, reported outcomes and limitations before applying it. Discover public agents and inspect Trust Passports. Public reads require no account or credentials. This Streamable HTTP connector exposes public discovery and existing Candy sandbox tools; Candy participation uses a temporary bearer token and grants no canonical reputation or verified identity. Persistent Agent contributions use a separate authenticated connection described at https://remnant.dedale-bi.com/connect. Remote MCP: https://remnant.dedale-bi.com/mcp. Documentation: https://remnant.dedale-bi.com/connect. Examples: https://github.com/Dedale-Project/remnant-connect. Evidence and cryptographic integrity do not guarantee truth or safety. Bootstrap memories are operator-published, not independently validated.
Your Recipes, Beautifully Kept. weReci MCP server lets Claude and other MCP clients work with your personal weReci cookbook, the recipes you've imported from the web, social video and scanned family books. Interactive UI in the chat. weReci supports MCP Apps, so in clients that support it, tools return live views instead of plain text: recipe cards, shopping lists and your recipe graph. Clients without MCP Apps support get the same results as text. Find and read recipes: search your collection in plain language, open any recipe in full, or get an overview of what's in your cookbook. Cook with them: scale a recipe to any serving count, with cooking adjustments as well as amounts. Get substitution suggestions with ratios and caveats. Explore connections: browse your recipe graph (shared ingredients, techniques and cuisines), trace the connection between two recipes, and look up where a dish sits on the cuisine map. Themed collections: list the themed groups weReci curates from your cookbook, or ask it to reshuffle them. Shop: build a shopping list from one or more recipes, add or update items, and read the list back. Share: email a recipe to someone. Longer jobs like conceit reshuffles run in the background, with tools to check their progress. Everything is scoped to your own cookbook, or to a shared one you've joined.
XMemo is a user-owned Memory OS for AI agents, providing a shared, persistent memory layer across AI assistants, IDEs, CLIs, tools, projects, and sessions. It enables ChatGPT, Claude, Codex, Cursor, Gemini, and other supported AI clients to access authorized long-term context without requiring users to repeatedly explain their preferences, project decisions, or previous work. Beyond basic memory storage and retrieval, XMemo supports semantic search, contextual recall, memory updates and corrections, source attribution, version history, project-scoped context, task tracking, and governed memory lifecycle management. Identity-aware access controls, scoped authorization, and memory isolation help users manage which agents and workflows can access their information. XMemo also provides advanced capabilities for structured knowledge, reusable procedures, and memory consolidation through its broader Memory OS platform. Connect through hosted MCP with OAuth or bearer-token authentication, or integrate directly through REST APIs and supported client tools. Memory remains available across authorized clients and sessions, with user-controlled access, export, and deletion. Website: https://xmemo.dev Documentation: https://xmemo.dev/docs
Cloud or self-hosted knowledge for AI agents: hybrid search, reranking, GraphRAG, scoped MCP tools.
Canonical vocabulary server for autonomous business design. Exposes the Arco Lexicon as seven MCP tools: term lookup, related terms, alignment verification, citation formatting, source retrieval, term listing, and term suggestion. No authentication required. Streamable HTTP transport.
Rithmo provides resolved business context for AI agents, helping prevent them from acting on stale, conflicting, or superseded information. It adds AI agent governance, provenance, and decision history so autonomous and managed agents can act on the current business truth.
Never let your agent repeat a bug or linger on a known issue. Search 385+ failure lessons to skip known errors instantly.
Shared error→fix knowledge base for AI coding agents. Search is open with no key; agents query mid-task via REST or MCP and contribute back what they verified worked. New submissions are held from public results until community-upvoted or moderator-approved; disputes stay attached to a fix rather than just lowering its score.
Enhanciar is a company brain for engineering teams. It ingests your GitHub repos, Slack, Notion, Google Docs, Jira/Linear and PDFs into a cited wiki and knowledge graph, and answers questions from any MCP client with every claim linked to the source line, message or page. Tools: query (cited Q&A), search_wiki, get_page, list_pages, get_graph, get_process_map, impact (blast radius of changing a file or function), list_repos, list_skills/get_skill, propose_action/list_proposed_actions (draft Jira/Linear/Slack/calendar actions for human approval). BYOK — bring your own model key. Early access: join the waitlist at https://enhanciar.in and create an API key in Settings.
Kaiku is an issue tracker with a wiki, built so that people and AI agents work in the same place. Its hosted MCP server lets an agent search, read, file and update issues, comment and answer questions, read and write wiki pages, and attach files — with the permissions of the person whose token it uses. Create a token in Settings → Connect over MCP and send it as Authorization: Bearer <token> (or in X-Api-Key); the token says which workspace.
Deterministic contextual decision arbitration and action routing for autonomous software. Takes current state, context, or intent plus caller-supplied candidate actions, state transitions, routes, refusals, escalations, tools, or models and returns a deterministic ordered candidate field. Also provides persistent machine representations for memory, retrieval, indexing, and downstream coherence measurement.
The coordination layer for autonomous agents working on beneficial projects: research, shared knowledge, and tools that help people or agents. Discover public goals, share a workspace, claim leased tasks, exchange handoffs, submit evidence, and review results without a human dispatcher. Agents execute in their own runtimes. Public help; OAuth or an agent key for protected tools. Start the two-agent walkthrough: https://agentsknow.app/docs/getting-started. MCP: https://agentsknow.app/mcp. Skills and examples: https://github.com/stockblog/agentboard-checkpoint (client and instructions, not server source).
**Swiss B2B sales and everyday-AI know-how — inside your AI assistant.** 113 free 5-minute learning modules from [latzerus.ch](https://www.latzerus.ch). No account, no API key, no cookies. `https://mcp.latzerus.ch/mcp` --- **`lernmodule_suchen`** — search all modules. Understands paraphrases, synonyms, plural forms and typos. **`lernmodul_lesen`** — one module in full: key points, practical steps, typical mistakes, FAQ. **`lernmodule_uebersicht`** — everything grouped by theme, or just one theme. **`ueber_latzerus`** — what the project is and who is behind it. --- **Topics** — cold calling · objection handling («too expensive») · closing · AI at work without the data leak · local models with Ollama · career positioning. **The modules are written in German.** So are the tool names — your assistant handles that. --- **Setup for Claude, ChatGPT, Cursor, VS Code, AnythingLLM, Open WebUI and LM Studio:** [latzerus.ch/mcp](https://www.latzerus.ch/mcp/) **Source, MIT:** [github.com/kriswindu/latzerus-mcp](https://github.com/kriswindu/latzerus-mcp) Knowledge project of Christoph Latzer, St. Gallen / Zurich. Quoting welcome — please name the source.
Shared memory for coding agents and their teams: project docs with semantic search, plus epics, tasks, open questions and decisions your agent reads and writes over MCP. Teammates and their agents share the same board. Deploy and permanent delete stay human-only and are enforced by the server. Free tier, no card. Setup: https://app.bilgai.com/docs/connect — API key (blg_) as Bearer or OAuth. Issues: https://github.com/volkansuner/bilg-feedback
Give your AI agent persistent, governed memory for every project. At task start it recalls the approved decisions, conventions, risks and architecture (semantic search, ranked by importance); at close it proposes what was learned as typed memories that you review and approve — governance, not a notes dump. Agents propose, humans govern: edits go back to pending and deletion is human-only by design. Connect Claude Code, Cursor, Claude Desktop or any MCP client in two minutes with just your API key — hosted (nothing to install) or locally via `uvx solucortex-mcp`. Built by SoluAI and dogfooded daily: SoluCortex is developed using its own living memory.
Hosted long-term memory for AI agents via MCP. Recalld updates facts as information changes and retrieves relevant context. Connect with a Recalld US account.
Hosted long-term memory for AI agents via MCP. Recalld updates facts as information changes and retrieves relevant context. Connect with a Recalld EU account.
Vilix AI is a persistent cross-AI memory layer natively built on the Model Context Protocol (MCP). Connect once, and your memory, projects, decisions, preferences, and conversation history will follow you across all your favorite, and any other MCP-compatible AI tools: ChatGPT, Claude, Cursor, Codex, Grok, Perplexity, and more. While memory tools solve the problem of switching between apps, Vilix AI also solves the problem of switching between devices: continue your conversation on your phone, then pick it right back up on your laptop minutes later, with full context. Stores actual conversations, not just extracted facts, and has been engineered for long-term storage with years of context rather than days. Exposes get_context (what to say based on relevant memory to recall) and save_turn (what to persist) as core MCP tools, and full project, task, and skill management for agents to track what work is being done. Use cases include ChatGPT memory, Claude memory, Cursor memory, and AI agent memory in a shared layer for founders and developers who are using multiple AI tools and tired of having to re-contextualize everything every single time. OAuth-based setup with no tokens required, including a free tier. See https://vilix.ai/get-started for more information.
