Add get_component_definition tool

[mathislucka]

Overview

We want to add a tool that can get the component definition of a single component by using the fully qualified component type (e.g. haystack.components.routers.conditional_router.ConditionalRouter). The tool should extract the requested component definition from the component schema and then return the component definition as a neatly formatted string.

Component definition

Here is an example of a component definition:

{'description': 'Converts XLSX (Excel) files into Documents.

    Supports reading data from specific sheets or all sheets in the Excel file. If all sheets are read, a Document is
    created for each sheet. The content of the Document is the table which can be saved in CSV or Markdown format.

    ### Usage example

    ```python
    from haystack.components.converters.xlsx import XLSXToDocument

    converter = XLSXToDocument()
    results = converter.run(sources=["sample.xlsx"], meta={"date_added": datetime.now().isoformat()})
    documents = results["documents"]
    print(documents[0].content)
    # ",A,B
1,col_a,col_b
2,1.5,test
"
    ```', 'properties': {'init_parameters': {'properties': {'read_excel_kwargs': {'_annotation': 'typing.Optional[typing.Dict[str, typing.Any]]', 'default': None, 'description': 'Additional arguments to pass to `pandas.read_excel`.
            See https://pandas.pydata.org/docs/reference/api/pandas.read_excel.html#pandas-read-excel', 'properties': {'_python_type': {...}}, 'type': ['null', 'object']}, 'sheet_name': {'_annotation': 'typing.Union[str, int, typing.List[typing.Union[str, int]], NoneType]', 'anyOf': [{...}, {...}, {...}, {...}], 'default': None, 'description': 'The name of the sheet to read. If None, all sheets are read.'}, 'store_full_path': {'_annotation': '<class 'bool'>', 'default': False, 'description': 'If True, the full path of the file is stored in the metadata of the document.
            If False, only the file name is stored.', 'type': ['boolean']}, 'table_format': {'_annotation': 'typing.Literal['csv', 'markdown']', 'default': 'csv', 'description': 'The format to convert the Excel file to.', 'enum': ['csv', 'markdown'], 'type': 'string'}, 'table_format_kwargs': {'_annotation': 'typing.Optional[typing.Dict[str, typing.Any]]', 'default': None, 'description': 'Additional keyword arguments to pass to the table format function.
            - If `table_format` is "csv", these arguments are passed to `pandas.DataFrame.to_csv`.
              See https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_csv.html#pandas-dataframe-to-csv
            - If `table_format` is "markdown", these arguments are passed to `pandas.DataFrame.to_markdown`.
              See https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_markdown.html#pandas-dataframe-to-markdown', 'properties': {'_python_type': {...}}, 'type': ['null', 'object']}}, 'required': [], 'type': 'object'}, 'type': {'component_frequency': 29, 'const': 'haystack.components.converters.xlsx.XLSXToDocument', 'family': 'converters', 'family_description': 'Convert data into a format your pipeline can query. Use a converter that matches your data type.', 'readme_link': 'https://docs.haystack.deepset.ai/docs/xlsxtodocument', 'type': 'string'}}, 'title': 'XLSXToDocument', 'type': 'object'}

We would fetch the component using: haystack.components.converters.xlsx.XLSXToDocument

The neatly formatted version of the definition should have:

• fully qualified component path
• component name
• component description
• init_parameters (inlcuding name, type and description)
• family and description

Make sure it is compact yet readable.

Steps

• check src/deepset_mcp/tools/haystack_service.py to see a comparable tool and add the get_component_definition tool in the same file
• you need to use the same call to fetch the component schema, then extract the requested component by fully qualified path
• errors should be returned as string
• add tests in test/unit/tools/test_haystack_service.py use the same testing style (fake resource)