# Seeds: The Foundation of myNeutron

Everything in myNeutron starts with a **Seed.**

> **A Seed is a Saved Piece of Knowledge.**

It captures what you save, upload, or sync and turns it into structured context your AI can use.

Each Seed acts like a memory cell for your personal AI brain.\
Together, they form your permanent, searchable memory inside myNeutron.

***

#### A Seed Could Be

* A webpage you saved
* A paragraph you highlighted
* A PDF, note, or image you uploaded
* An email or file synced from Gmail or Drive

***

#### Each Seed Contains

* **Original Content:** Text, media, or data you added
* **Metadata:** Title, source, date captured, type, and tags
* **AI Embeddings:** Semantic representation for deep search and recall
* **Context Links:** Relationships between similar or related Seeds

Your Seeds form a living, connected memory graph.\
myNeutron and your connected AIs can query, learn from, and summarize this graph.

***

#### Why Seeds Matter

Traditional notes and files stay static.\
Seeds are portable, searchable, and ready for AI use.\
They can be accessed by any AI tool through myNeutron’s **Model Context Protocol (MCP).**

| Without myNeutron             | With myNeutron                         |
| ----------------------------- | -------------------------------------- |
| Notes stay trapped in one app | Knowledge is portable across tools     |
| Search is keyword-based       | Search understands meaning and context |
| Files and emails are separate | All unified as Seeds in one workspace  |


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://neutron-4.gitbook.io/neutron-docs/getting-started/seeds-the-foundation-of-myneutron.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.