Removes an existing index add_document WRITE_DOCUMENTS Adds a document to the index delete_document WRITE_DOCUMENTS Removes a document from the index query_index READ_DOCUMENTS Searches a specific index to retrieve matching documents get_document_count READ_DOCUMENTS Returns the total number of documents in the index list_indexers READ_INDEXER Retrieve all names of indexers from the AI Search Service get_indexer READ_INDEXER Retrieve the full definition of a specific indexer from the AI Search Service create_indexer WRITE_INDEXER Create a new indexer in the Search Service with the skill, index and data source delete_indexer WRITE_INDEXER Delete an indexer from the AI Search Service by name list_data_sources READ_INDEXER Retrieve all names of data sources from the AI Search Service get_data_source READ_INDEXER Retrieve the full definition of a specific data source list_skill_sets READ_INDEXER Retrieve all names of skill sets from the AI Search Service get_skill_set READ_INDEXER Retrieve the full definition of a specific skill set

MCP Service Tool Groups

We do not want your MCP Host to be overwhelmed with the amount of tools coming from this service.

These are the available tool groups and their purposes:

READ_OPERATIONS - tools used for read-only operations
WRITE_OPERATIONS - tools that are used for creating, modifying or removing entries. Alias for ALL
READ_INDEX - tools used to list and describe the indices in the service
WRITE_INDEX - tools used to Create, delete, update, or configure indices
READ_DOCUMENTS - tools used to query the indices to retrieve documents
WRITE_DOCUMENTS - tools for Adding, Updating or Deleting documents from an index
WRITE_INDEXERS - tools used to configure indexers, data sources & skill sets
READ_INDEXERS - tools used to retrieve information about data sources, skill sets and indexers

Pre-Requisites

You will need to have configured a Service Principal that will be used to authentic against the AI Search service you are interacting with. You may also use the AI Search Key with read/write privilleges on the index dependening on what capabilities you are looking to leverage from the service.

Python 3.12 or later is needed, and you have to install uv as well to leverage the service.

The repository below contains a Terraform script that can accelerate the provisioning of an AI Search service and service principal necessary to help you get started.

Installing Dependencies

Follow the links below to install uv, python and the module containing the MCP service

You can install the mcp service as follows:


uv build

pip install dist/mcp_server_azure_ai_search_preview-0.3.1-py3-none-any.whl 

# If you are running in SSE mode, you can run it as:
uv run -m mcp_server_azure_ai_search_preview --transport sse --envFile .env --host 127.0.0.1 --port 8000

#f you are running it in STDIO mode in Cursor or Claude Desktop, we have an example config below for you to use

The environment file, host and ports are optional. The default values will be used if you do not specify them

You can also clone this git repo and install the service via the main.py file in this repo

Confi

Categories

Current Category: ai-search

mcp-server-azure-ai-search-python-preview

coco-app