> ## Documentation Index
> Fetch the complete documentation index at: https://docs.bland.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Create a Knowledge Base

> Create a new knowledge base.

Usage: Pass the `vector_id` into your agent's `tools` to enable the agent to use the vector store.

```json theme={null}
"tools": [
    "KB-55e64dae-1585-4632-ae97-c909c288c6bc"
]
```

### Headers

<ParamField header="authorization" type="string" required>
  Your API key for authentication.
</ParamField>

### Body

<ParamField body="name" type="string" required>
  The name of the knowledge base. Make this a clear name that describes the contents of the store.
</ParamField>

<ParamField body="description" type="string" required>
  A description of the knowledge base. This can be a longer description of the contents of the store, or what terms to use to search for vectors in the store.

  This is visible to the AI, so making it descriptive can help the AI understand when to use it or not.
</ParamField>

<ParamField body="text" type="string" required>
  The full text document to be stored and vectorized.
</ParamField>

### Response

<ResponseField name="vector_id" type="string">
  The unique identifier for the knowledge base.

  Will start with "KB-".
</ResponseField>

<ResponseExample>
  ```json theme={null}
  {
    "vector_id": "KB-55e64dae-1585-4632-ae97-c909c288c6bc"
  }
  ```
</ResponseExample>

***

Docs for agents: [llms.txt](/llms.txt)