Skip to main content
This guide covers how to create and manage Knowledge Bases (KBs), index and de-index content for semantic search, perform searches, and manage Entities and Relationships. For agent integration using MCP tools, see the MCP guide.

​
Create and manage Knowledge Bases

Use the Catalog API to create, list, update, and delete KBs. 
POST /v1/catalog/knowledge-bases
{
  "name": "product-docs",
  "displayName": "Product Documentation",
  "description": "Technical documentation and guides",
  "enabled": true
}

GET /v1/catalog/knowledge-bases

GET /v1/catalog/knowledge-bases/:idOrName

PATCH /v1/catalog/knowledge-bases/:idOrName
{
  "displayName": "Docs",
  "enabled": true
}

DELETE /v1/catalog/knowledge-bases/:idOrName

​
Notes

  • Each KB has an isolated vector collection.
  • Default KB “general” exists for every organization.

​
Index and de-index content

Index Entities asynchronously and Relationships synchronously into the KB’s vector store. 
POST /v1/search/index
{
  "entity": {
    "type": "Document",
    "content": { "type": "text", "text": "This is the content..." },
    "properties": { "title": "Getting Started" }
  },
  "kb": "product-docs"
}

POST /v1/search/index/connect
{
  "relationship": { "type": "references" },
  "source": { "id": "ent_123" },
  "target": { "id": "ent_456" },
  "kb": "product-docs"
}

POST /v1/search/deindex
{
  "id": "ent_123",
  "objectType": "Entity", // or "Relationship"
  "kb": "product-docs"
}

​
Tips

  • Large files should be indexed asynchronously.
  • Provide meaningful properties (e.g., title, category) to improve filtering.
Perform semantic search across Entities and Relationships within a KB. 
POST /v1/search
{
  "query": "how to implement authentication",
  "kb": "product-docs",
  "limit": 10,
  "objectType": "Entity",
  "types": ["Document", "Guide"],
  "properties": { "category": "documentation" }
}

​
Features

  • Vector similarity ranking with configurable score threshold
  • Filtering by object type, types, and properties
  • Pagination with limit/offset

​
Manage Entities and Relationships

Entities represent nodes (documents, objects) with content and metadata. Relationships connect Entities. 
POST /v1/entities
{
  "knowledgeBaseId": "kb_abc123",
  "type": "Document",
  "externalId": "doc-123",
  "content": { "type": "text", "text": "This is the document content..." },
  "properties": { "title": "Getting Started", "category": "documentation" }
}

POST /v1/relationships
{
  "type": "references",
  "sourceId": "ent_123",
  "targetId": "ent_456",
  "properties": { "notes": "Cites paragraph 2" }
}

​
Guidance

  • Choose appropriate entity types; keep property schemas consistent.
  • Use timestamps for time-aware queries.

​
MCP tools (overview)

Agents can access KBs and perform search via MCP tools (covered in-depth separately). You can: list KBs, run semantic search, and execute query models from an agent environment. See the MCP guide for setup and examples.