Azure Cognitive Search

Azure Cognitive Search MCP Connector for Claude

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Empower your AI with enterprise retrieval — run full-text search, semantic queries, and inspect cognitive skillsets on your Azure indexes.

7 tools Official Updated Jun 28, 2026 Official Vinkius Partner

Connect your Azure Cognitive Search endpoints to any AI agent and bring the power of enterprise information retrieval directly into your conversational workflows.

What you can do

  • Deep Search & Point-Reads — Execute full-text lexical queries across indexes or extract an exact, specific document mapping using its explicit UUID key
  • Vector Retrieval — Inject structural arrays into predefined embedding domains for accurate, multidimensional K-Nearest Neighbor mapping
  • Indexers & Skillsets — Discover active background tasks routing Azure blobs or databases, and inspect active Cognitive Services orchestrating OCR and text enrichment
  • Schema Definitions — Trace exact token analyzers and dimensional shapes securing your cloud's query behaviors natively

How it works

  1. Subscribe to this server
  2. Enter your Azure Search Endpoint and proper API Key
  3. Start querying or debugging the orchestration structure immediately from Claude, Cursor, or your MCP interface

Who is this for?

  • Search Architects — test advanced BM25 parameters, vector similarities, and fetch distinct raw items without compiling secondary tools
  • Data Engineers — ensure the active indexers are successfully pulling documents and that cognitive skillsets (like translation or OCR) are deployed
  • Machine Learning Ops — compare index schema changes and experiment iteratively with retrieval techniques
cognitive-searchsemantic-queriesdata-retrievalcloud-infrastructureindex-management

7 tools expose this connector's capabilities to your AI agent.

list_indexes

List Azure Search indexes

get_index

Get Azure Cognitive Search index details

search_documents

Execute lexical full-text queries against Azure cognitive indexes

vector_search

Perform structural KNN vector searches against Azure embedding profiles

get_document

Retrieve an exact single document mapped explicitly by its UUID key

list_indexers

List explicitly scheduled Azure Search indexers

list_skillsets

List Cognitive Services skillsets orchestrating text enrichments

See how to talk to your AI agent using Azure Cognitive Search.

Use the Get Document tool to show me the full raw JSON of record 'abc-1234'.

I retrieved the exact target doc 'abc-1234' from the 'employees' index. It includes 14 metadata fields, no vector map defined internally, and specifies the timestamp of ingestion. Here's a brief breakdown of its financial contents...

List active Indexers and tell me if the blob-syncher is functioning.

I checked the 3 Azure Search indexers set up. The 'blob-syncher' ran 10 minutes ago, reporting a clean 200 success code. However, the 'sandbox-test-indexer' has been stalled for 48 hours waiting on database connection string issues.

List all active skillsets enhancing our search environment currently.

You have a single configuration skillset named 'ocr-and-translate' applied. It chains out the Azure Cognitive Vision API to extract image text seamlessly and subsequently forces Language Service mapping toward default EN tokens via integration.

Yes! Unlike complex search endpoints, this provides a point-read mechanism (Get Document). Your agent maps the target UUID and bypasses search algorithms completely, quickly delivering the raw JSON of that exact specific item for isolated deep reading.

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