AgentBrains Knowledge Base
Retrieve exact documents, categories, images, relationship metadata, and company data from AgentBrains.
AgentBrains Knowledge Base
Use this node when the workflow must read the exact record you curated in AgentBrains instead of relying on semantic search alone.
This node is designed for deterministic retrieval:
- price lists
- product specification sheets
- instruction manuals
- customer support policies
- image assets attached to knowledge base entities
Why this node matters
If the workflow already knows the category, document family, or exact record it needs, deterministic retrieval is usually better than broad search. It reduces hallucinations and gives downstream LLM steps cleaner, more controlled context.
Resources and operations
The node exposes several resource types through a single interface.
| Resource | What it returns | Available operations |
|---|---|---|
| Documents | Knowledge base entities such as documents, products, or services | Get, Get Many, Get Related Entities, Get by Category Type, Get All Documents |
| Category | Folder-like groupings used to organize entities | Get, Get Many, Get by Type |
| Images | Attachments and media linked to entities | Get Many, Get |
| Company Data | High-level company profile fields | Direct fetch without an operation selector |
Relationship type and category type values still appear where they are used as filters or operation inputs, but they are not standalone resources in the node.
Core parameters
Documents
| Parameter | Used in | Description |
|---|---|---|
| ID | Get, Get Related Entities | Fetch a specific entity or use it as the source for relationship lookup |
| Category Names or IDs | Get Many | Filter documents by one or more categories selected from the dropdown |
| Search | Get Many | Case-insensitive search across name, description, and details |
| Recursive | Get Many | Include documents from nested categories under the selected category |
| Category Type Name or ID | Get by Category Type | Query documents by category alias, such as a document family |
| Additional Fields | Get Many, Get by Category Type | Filter with fields, sku, source, or tags |
| Merge Documents | Get All Documents | Combine many document records into one mergedContent output |
Categories
| Parameter | Used in | Description |
|---|---|---|
| ID | Get | Fetch a single category |
| Category Type Name or ID | Get by Type | List categories belonging to one category alias |
| Additional Fields | Get Many | Filter with categoryAlias, policy, parent, search, fields, and extended |
Images and metadata
| Parameter | Used in | Description |
|---|---|---|
| ID | Get | Fetch a single attachment by ID |
| Additional Fields | Get Many | Restrict the response fields for image records |
Output behavior
The node returns slightly different shapes depending on the operation:
| Operation type | Output shape |
|---|---|
| Single record operations | A normal object for the entity, category, image, or company data |
| List operations | An object with an items array |
| Get All Documents with Merge Documents enabled | A single object with mergedContent and documentCount |
That output shape is useful in n8n because list responses stay explicit and easy to pass into later branching or formatting steps.
Best use cases
Exact policy retrieval
Use Documents with category filters when the workflow must quote a known policy, instruction manual, or price list exactly as it exists in AgentBrains.
Structured product lookup
Use Documents with sku, search, or tags when the workflow already has a product identifier and needs the cleanest possible source record.
Folder-driven browsing
Use Category to build UI-like selection logic inside n8n, especially if you want users or agents to choose from known document families.
Image access
Use Images when the workflow needs attachment metadata or an asset already linked to a document entity.
Company context
Use Company Data to fetch tenant-level profile data such as business context for personalization or routing.
Node Interface
Here is how the AgentBrains Knowledge Base node looks in n8n:
Practical examples
Retrieve a strict source document
Select:
- Resource: Documents
- Operation: Get Many
- Category Names or IDs: a folder like instruction manuals or support policies
- Search: an exact product or topic phrase
This is the best setup when the answer should come from a known document family and not from broad semantic search.
Build one prompt from many documents
Select:
- Resource: Documents
- Operation: Get All Documents
- Merge Documents: enabled
This produces one combined body of content that can be sent into an LLM or stored as a downstream artifact.
Find all related items
Select:
- Resource: Documents
- Operation: Get Related Entities
- ID: source entity ID
- Additional Fields → Type: optional relationship type like
is-accessory-for
This is useful for recommendation, upsell, troubleshooting, or related-document flows.
API concepts behind the node
The node is backed by the AgentBrains integration layer for knowledge-base scope. It maps to:
- entity listing and entity-by-ID retrieval
- category listing and category-alias discovery
- attachment retrieval
- helper company-info retrieval
The OpenAPI specification for the underlying data APIs confirms the same filtering model used in the node, including search, fields, tags, sku, source, and recursive category traversal.
Knowledge Base vs RAG
Use this node when you know what should be fetched. Use AgentBrains RAG when the agent only knows the user intent and must semantically search across an index first.