MyAITwin

com.lutolearnPublished by lutolearn.comOfficial publisherv1.0.0Updated Oct 26, 2026

A personal RAG database you build from chat, so AI creates work that sounds like you.

VerifiedStreamable HTTPWeb executableDatabases Knowledge & Memory

Server details

Identifier: com.lutolearn/myaitwin
Transport: Streamable HTTP
Runtime: Web executable
Trust: Verified
Published: Sep 16, 2026

Security note

MCP servers receive tool arguments from a conversation and may perform external actions. Review what a server can do before you enable it, and give it only the access it needs.

The registry verified that this server's namespace belongs to lutolearn.com, which also runs its endpoint. That identifies the publisher; it does not make the server's tools safe.

SourceWeft's checks cover whether the listing is complete and the endpoint answered; they do not review the server's code or what its tools do.

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Overview

AI-generated overview

A personal RAG database and semantic search service that lets an assistant store your knowledge and writing style, then retrieve them with cited sources.

What you can do: Store knowledge items, voice notes, long documents, fetched web pages and creation records
Search semantically across all knowledge, or search skills and knowledge separately for a creation task
Retrieve items by type, by tag, or list recent additions
Inspect the schema and sources, surface recurring patterns, and synthesise across items on a topic
Manage the twin: initialise a session, update items, define or update knowledge types, and delete items
When to use it: Useful when you want an assistant to produce work that reflects your own material and voice across conversations, such as drafting a follow-up email from a meeting transcript using your stored email style. Suited to people who are willing to build and curate a personal knowledge base from inside chat.
Requirements: A remote MCP endpoint over Streamable HTTP at the provider's /mcp URL, with OAuth 2.1 (PKCE, dynamic client registration) sign-in. An account created by email via a magic link, and a client with MCP capability; the README names Claude Pro, Claude Team and ChatGPT Pro. No environment variables or headers are declared.

Before you install

Stored content is sent to and kept by the provider, which describes Supabase and Pinecone as its storage layers; the README says data is not used for training or shared with third parties. Most tools write data, and delete_knowledge is destructive. Account deletion is described as immediate and irreversible. The service is free only during early access, so terms may change.

Installation

In SourceWeft

Open MyAITwin in the dashboard and add it to a workspace.
Connect the required credentials. They are stored privately and never shown on public pages.
Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/com.lutolearn%2Fmyaitwin/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config. The client completes OAuth sign-in on first connect.

{
  "mcpServers": {
    "myaitwin": {
      "type": "http",
      "url": "https://myaitwin.lutolearn.com/mcp"
    }
  }
}

README

MyAITwin MCP

A personal RAG database and semantic search engine you build and control from inside your AI chat. Store your knowledge, voice, and skills as you work. Retrieve them in seconds, source always cited. Your AI then creates output that is recognisably you, in every conversation.

Live at https://myaitwin.lutolearn.com. Free during early access.

What it is

MyAITwin is two things at once.

The toolbox. A production-grade RAG database with semantic search that you shape from chat. You define the structure, the types, the tags. It is yours, it is visible, and you are the architect of it.

The twin. The layer on top that greets you, guides you, assesses what you store, and creates output that sounds like you. It knows the difference between what you know (your knowledge) and how you say things (your skills), and it uses both.

Install

Three steps. Under two minutes.

Sign up at https://myaitwin.lutolearn.com/ with your email.
Click the magic link, then copy your personal MCP URL from /create.
In Claude Desktop: Settings → Connectors → Add custom connector → paste your URL.

Or use the canonical OAuth-authenticated endpoint:

URL: https://myaitwin.lutolearn.com/mcp
Transport: Streamable HTTP
Auth: OAuth 2.1 with PKCE (S256) and Dynamic Client Registration

Requires a client with MCP capability. Currently Claude Pro, Claude Team, and ChatGPT Pro.

The 19 tools

Storing knowledge

Tool	What it does
`add_knowledge`	Store a typed, tagged knowledge item
`add_voice_note`	Store a voice note transcript with automatic extraction
`add_document`	Store a long document with automatic chunking
`add_from_url`	Fetch and store a web page
`add_reference_record`	Store a creation event linking knowledge and skills used

Retrieving knowledge

Tool	What it does
`search_twin`	Semantic search across all knowledge
`search_for_creation`	Dual search returning skills and knowledge separately
`get_by_type`	Retrieve all items of a specific type
`get_by_tag`	Retrieve all items with a specific tag
`list_recent`	List recently added items

Understanding your twin

Tool	What it does
`get_schema`	Overview of your types and how many items you have
`get_sources`	List all source documents
`find_patterns`	Surface recurring patterns across your knowledge
`synthesise`	Synthesise across multiple knowledge items on a topic

Managing your twin

Tool	What it does
`get_welcome`	Session initialisation and system prompt
`update_knowledge`	Update an existing item
`add_schema_type`	Define a new knowledge type
`update_schema_type`	Update an existing type definition
`delete_knowledge`	Delete an item (destructive)

All tools are annotated with title, readOnlyHint, and destructiveHint per the MCP spec. Of the 19: 10 read-only, 8 write (non-destructive), 1 destructive (delete_knowledge).

How it works

RAG is Retrieval-Augmented Generation. It is the architecture that lets AI answer using your specific knowledge rather than its training data alone.

Two layers:

Supabase (PostgreSQL) for structured records with types, tags, and provenance.
Pinecone for vector embeddings, so you can search by meaning rather than exact words.

When you search, both layers work together and return results ranked by relevance. Every result is cited with source and date, and tagged with provenance: personal (your own thinking), organisational (from your organisation), or external (from someone else).

The architectural insight worth getting right:

Knowledge is what you know. Facts, decisions, transcripts, observations.

Skills are how you express things. Your LinkedIn voice. Your email style. Your proposal structure.

Exceptional output needs both. Take a meeting transcript and ask for a follow-up email. The twin needs the transcript and your email skill to produce something that is accurate and unmistakably yours. Neither alone is enough.

Security and privacy

Bearer token authentication on every request, hashed at rest.
OAuth 2.1 with PKCE for connector-style integration. No shared secrets, no static credentials.
Multi-tenant data isolation: each user lives in their own namespace. Other users can never read your data. Verified by a 35-check cross-tenant test suite.
Rate limiting per tenant.
Append-only audit log on every tool call.
Prompt injection guardrails on stored content.
Your data is used only to provide the service. Never used to train AI models. Never shared with third parties.
You can delete your account and all data instantly from /create. Deletion is immediate and irreversible.

Privacy policy: https://myaitwin.lutolearn.com/privacy Security contact: [email protected] Privacy contact: [email protected]

Distribution

Official MCP Registry: com.lutolearn/myaitwin
Anthropic Connectors Directory: submitted, in review
Listed at: Glama, mcp.so, mcp.directory, mcpserverfinder, Hugging Face, awesome-mcp-servers

License

MIT. See LICENSE.

Tools

This server asks you to sign in, so SourceWeft could not read its tools without an account and has not indexed them. What a connected account sees can depend on that account and its permissions.

Version history

v1.0.0LatestSep 16, 2026

Score

75% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

Reached in the last 30 daysRequired25 pts
Auth declaredRequired10 pts
Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
DescriptionRequired15 pts
Logo10 pts
Documentation15 pts
License10 pts
Declare a license in the repository or the registry entry.