What your vault knows. What Mandaire knows.

Obsidian is a thinking tool. It knows what you write, when you write it. That is the right design for notes. It is the wrong design for a personal AI that needs to reason about your relationships, your history, and the full arc of your working life.

Mandaire indexes the history you have already accumulated, without requiring you to write anything new.

Source Obsidian vault Mandaire
Notes you deliberately write Yes Yes, via capture or extension
20+ years of email (Gmail / iCloud) No Yes
iMessage history No Yes, via local bridge
WhatsApp threads No Yes
Apple Notes No Yes
Calendar history and attendees No Yes
ChatGPT conversation history No Yes, via export ingest
Claude and Gemini conversation history No Yes, via export ingest
LinkedIn connections No Yes
Photos (people, events, context) No Yes

The structural difference: Obsidian is a tool for notes you actively author. Mandaire is a context layer built from the data trail your life already produces. They are compatible, not competing. If you have years of Obsidian notes, Mandaire can surface them alongside your email, messages, and AI sessions in a single MCP tool call. You do not have to choose.

The person problem.

Your vault may have notes about Maya Patel, your former collaborator. Your email has 340 threads. WhatsApp has a group where she appears under a different number. Your calendar has 12 meetings. Your Claude conversations reference "the Maya project" without naming her directly.

The Obsidian + Claude Code pattern cannot connect these. Each source is a separate island. When you ask "what do I know about Maya," you are asking against your notes only.

Mandaire resolves these into a single entity across sources, using a five-phase pipeline: canonical normalization, inverted-index matching, multi-feature scoring across email addresses, phone numbers, and display names, alias-overlap merge, and UUID assignment. A single entity survives alias drift across every source. The "Maya" in your iPhone contacts and the "[email protected]" in your email archive resolve to one person with a unified 20-year history. From that resolution, Mandaire builds the graph that answers the questions that actually matter: who Maya is in your life, what she cares about based on 20 years of interaction patterns, what your relationship with her looks like, what you typically share with her, and which claims about her across your sources are reliable enough to act on.

The thing DIY cannot assemble.

Even a well-assembled Obsidian vault with MCP access gives every AI tool the same view of your context. There is no concept of "Sam Nakamura is allowed to see my availability but not my financial situation" or "this reply to Jordan Chen should not surface information from a thread Jordan is not part of."

Mandaire has a disclosure layer built in. Every MCP response is filtered per the recipient, topic, context, and surface it is being requested for. You do not configure this by writing policy files; you configure it by using the system and letting it learn from your corrections.

Without Mandaire

Your AI gets the full context you have assembled. Every tool call returns the same view. You manage what you share in the prompt. This is not a failure of Obsidian; it is not designed for this problem.

With Mandaire

Each MCP call is evaluated against who is asking, what they are asking about, in what context, and on what surface. The same question from two different people can produce structurally different responses, without you writing a policy for every case.

Local-first means different things.

Obsidian is genuinely local-first: your vault is files on your machine. That is the right starting point. The question is what connects to those files and under what terms.

When you use Claude Code or any other AI client against your vault via MCP, that client sends your content to the AI provider. The context is local until it is not. This is not a criticism of Obsidian; it is the architecture of every AI client.

Mandaire runs on a private server under your control, with your data encrypted at rest. The AI client you use reads from Mandaire's MCP interface; it does not receive your raw email archive or message history. It receives a filtered, resolution-aware response. The raw corpus stays on your server.

This distinction matters if your context contains anything you would not want indexed in an AI provider's training pipeline or accessible via a compromised account.

Connect your first source in five minutes.

Mandaire installs as an MCP tool in Claude, ChatGPT, or any compatible client. Your Obsidian workflow does not change. You add one MCP connection, and your AI can now see the 20 years of context your vault cannot reach.