> ## Documentation Index
> Fetch the complete documentation index at: https://open-index.io/llms.txt
> Use this file to discover all available pages before exploring further.
# Open Index
> Build domain-specific, structured context that agents can actually operate on — and keep it correct as things change.
**Open Index** is a tool for building domain-specific, accurate, structured data
that agents can actually operate on — and for keeping that data correct as things
change.
You use Open Index to build a **brain**: a searchable, continuously-improving
context graph of your domain. A brain is **domain-agnostic** — model a support org
(`product → "has common issue" → issue`), a sales pipeline (`customer → order`),
your infrastructure (`service → runbook`), or anything else. You define the
concepts; Open Index stores them, searches them, and draws the map.
If this is useful, a star helps others find it — and helps us keep building in the open.
Install, spin up the bundled example brain, and open the explorer in a few minutes.
doc\_type, doc\_schema, entity, connector — the four primitives a brain is built from.
Define doc\_types, author entities, and load them into the search index.
Expose the brain over MCP so agents can read context and keep it current.
## What a brain is built from
A brain is built from four primitives:
* **doc\_type** — a concept you want to track and maintain (e.g. `service`, `customer`, `issue`).
* **doc\_schema** — the fields stored for a given doc\_type.
* **entity** — one instance of a doc\_type, stored per its schema. Every entity can
link to others via `related_to` (the target) + `relationship_edge_meaning` (free-text edge semantics).
* **connector** — an optional source you extract entities from (e.g. an MCP server).
## A context layer for domain-specialized agents
Open Index is designed to sit behind agents specialized for a domain — legal,
marketing, customer support, sales, infrastructure, or a domain of your own. The
MCP server gives those agents structured context and a validated way to keep that
context current:
* **agent prompt** — dynamic domain navigation is published through MCP server
instructions so supporting hosts can inject it before the first turn.
* **read** — `navigation_guidelines()` refreshes those instructions;
`search_brain()` and `get_entity()` retrieve domain context.
* **write** — `put_entity()` (add/update an entity), `create_doc_type()` (define a concept).
Read and write is the default MCP mode, so a domain agent can both use knowledge
and maintain it. Add `--read-only` when the agent should consume context without
mutating it.
Ask questions, share the brains you're modelling, or discuss an idea before you build it.