List Collections
Retrieve all available data collections from Hyperspell to connect AI applications with unstructured and semi-structured information sources.
Instructions
Get a list of all collections on Hyperspell
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Implementation Reference
- src/hyperspell_mcp/server.py:99-103 (handler)The handler function for the 'List Collections' tool, which fetches and returns the list of collections from the Hyperspell API using the Collection model.
@mcp.tool_or_resource("collection://", name="List Collections") def list_collections() -> list[Collection]: """Get a list of all collections on Hyperspell""" r = mcp.api.collections.list() return Collection.from_pydantic(r.items) - src/hyperspell_mcp/types.py:31-35 (schema)The Collection dataclass schema used for the output of the 'List Collections' tool, with from_pydantic conversion.
@dataclass class Collection(BaseModel): name: str documents_count: int = 0 - src/hyperspell_mcp/server.py:99-99 (registration)Decorator registering the tool with name 'List Collections' and URI 'collection://', which conditionally adds it as tool or resource.
@mcp.tool_or_resource("collection://", name="List Collections") - src/hyperspell_mcp/types.py:17-29 (helper)The from_pydantic classmethod used by Collection to convert API responses to the dataclass format.
@classmethod def from_pydantic( cls, model: PydanticBaseModel | Sequence[PydanticBaseModel] ) -> Self | list[Self]: """Convert a Pydantic model to a data class, selecting only the keys that are part of the data class.""" if isinstance(model, Sequence): return [cls.from_pydantic(m) for m in model] data = model.model_dump() # Only select the keys in data that are part of this data class data = {key: value for key, value in data.items() if key in cls.__annotations__} return cls(**data)