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

# List Knowledge Bases

**GET `/api/projects/{project_name}/knowledge_bases`**

This API endpoint lists all available knowledge bases using the `GET` method.

<Tip>
  Learn more about knowledge bases following [this doc page](/mindsdb_sql/knowledge_bases/overview).
</Tip>

### Path Parameters

<ParamField body="project_name" type="string" required>
  Defines the project where the knowledge bases are located. Note that the default project name is `mindsdb`.
</ParamField>

### Body

None.

### Response

<ResponseField name="id" type="string" required>
  Unique identifier for the knowledge base.
</ResponseField>

<ResponseField name="name" type="string" required>
  The name assigned to the knowledge base.
</ResponseField>

<ResponseField name="project_id" type="string" required>
  The ID of the project where the knowledge base resides.
</ResponseField>

<ResponseField name="project_name" type="string" required>
  The name of the project where the knowledge base resides.
</ResponseField>

<ResponseField name="vector_database" type="string" required>
  The vector store used for storing vector embeddings.
</ResponseField>

<ResponseField name="vector_database_table" type="string" required>
  The name of the collection or table within the vector database.
</ResponseField>

<ResponseField name="updated_at" type="string" required>
  Timestamp indicating when the knowledge base was last updated.
</ResponseField>

<ResponseField name="created_at" type="string" required>
  Timestamp indicating when the knowledge base was created.
</ResponseField>

<ResponseField name="query_id" type="string" required="false">
  Optional field for linking specific queries to this knowledge base.
</ResponseField>

<ResponseField name="embedding_model" type="string" required="false">
  The embedding model used to convert content into vector representations.
</ResponseField>

<ResponseField name="reranking_model" type="string" required="false">
  Optional model used to rerank search results based on relevance.
</ResponseField>

<ResponseField name="metadata_columns" type="list" required="false">
  Optional list of columns used for metadata-based filtering or enrichment.
</ResponseField>

<ResponseField name="content_columns" type="list" required="false">
  Optional list of columns treated as the main content for embedding and retrieval.
</ResponseField>

<ResponseField name="id_column" type="string" required="false">
  The name of the column that uniquely identifies each content row.
</ResponseField>

<ResponseField name="params" type="object" required="false">
  A nested object that contains additional configuration parameters.
</ResponseField>

<ResponseField name="params.created_embedding_model" type="string" required="false">
  The name of the embedding model associated with this knowledge base at creation time.
</ResponseField>

<ResponseField name="params.default_vector_storage" type="string" required="false">
  The default storage used for storing vector data.
</ResponseField>

<RequestExample>
  ```shell Shell theme={null}
  curl -X GET http://127.0.0.1:47334/api/projects/mindsdb/knowledge_bases
  ```
</RequestExample>

<ResponseExample>
  ```json Response theme={null}
  [
    {
      "id": 1,
      "name": "my_kb",
      "project_id": 1,
      "vector_database": "my_kb_chromadb",
      "vector_database_table": "default_collection",
      "updated_at": "2025-06-25 13:04:01.864625",
      "created_at": "2025-06-25 13:04:01.864624",
      "query_id": null,
      "embedding_model": null,
      "reranking_model": null,
      "metadata_columns": null,
      "content_columns": null,
      "id_column": null,
      "params": {
        "created_embedding_model": "kb_embedding_my_kb",
        "default_vector_storage": "my_kb_chromadb"
      },
      "project_name": "mindsdb"
    }
  ]
  ```
</ResponseExample>