Azure Cognitive Search Connector for AI agents.
7 live capabilities
Query and manage enterprise cloud search indexes from your AI client.
Waiting for input…
Why people use Azure Cognitive Search
Azure Cognitive Search for Cloud Data Retrieval
With this Connector, you just ask your agent to check the 'blob-syncher' or list your active skillsets. It gives you the status and the details in one go, letting you stay focused on the actual logic instead of the infrastructure plumbing.
What Vinkius changes
You get a direct interface for managing and querying Azure search without leaving your chat window.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Debugging a stalled sync
An engineer asks the agent to check the status of the 'blob-syncher' indexer to see why data isn't appearing in the search results.
- Real-world use case 02
Validating OCR output
A developer uses list_skillsets to confirm that the vision API is correctly extracting text from image blobs in their pipeline.
- Real-world use case 03
Rapid schema prototyping
A search architect compares the schema of two different indexes to ensure token analyzers match before a production rollout.
Complete set · 7capabilities
The complete Azure Cognitive Search capability set.
These are the exact actions your AI can choose when you ask it to work with Azure Cognitive Search.
01—04
4 capabilities in this set.
Part of 7 available through Azure Cognitive Search.
- 01 Capability
List indexes
See all your Azure Search indexes in one list. This helps you quickly identify which index you need to query.
- 02 Capability
Get index
Pull the specific details and configuration for a single index. Use this to check your schema and token analyzers.
- 03 Capability
Search documents
Run lexical full-text queries against your cognitive indexes. This is the primary way to find text based on keywords.
- 04 Capability
Vector search
Perform structural KNN vector searches against your embedding profiles. This handles multidimensional data mapping.
05—07
3 capabilities in this set.
Part of 7 available through Azure Cognitive Search.
- 05 Capability
Get document
Grab one exact document using its specific UUID key. It's the fastest way to see the raw JSON of a single record.
- 06 Capability
List indexers
See all scheduled Azure Search indexers and their current status. Use this to find stalled or failed sync tasks.
- 07 Capability
List skillsets
View the cognitive services skillsets orchestrating your text enrichment. This lets you see active OCR or translation tasks.
Set up in minutes
One URL. Then ask Azure Cognitive Search to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Azure Cognitive Search from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_hdKYLP4Ky0e0ym1FqqZkykLxQEDMxyTOrt4HuJb3/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Azure Cognitive Search, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Azure Cognitive Search for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_hdKYLP4Ky0e0ym1FqqZkykLxQEDMxyTOrt4HuJb3/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Azure Cognitive Search URL.
- Step 03
Save and start
Save the connection and enable Azure Cognitive Search in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"azure-cognitive-search": {
"url": "https://edge.vinkius.com/vk_preview_hdKYLP4Ky0e0ym1FqqZkykLxQEDMxyTOrt4HuJb3/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Azure Cognitive Search
Open Agent mode in chat and ask: "Using Azure Cognitive Search, help me...". 7 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"azure-cognitive-search": {
"url": "https://edge.vinkius.com/vk_preview_hdKYLP4Ky0e0ym1FqqZkykLxQEDMxyTOrt4HuJb3/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Azure Cognitive Search
Ask Copilot: "Using Azure Cognitive Search, help me...". 7 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"azure-cognitive-search": {
"url": "https://edge.vinkius.com/vk_preview_hdKYLP4Ky0e0ym1FqqZkykLxQEDMxyTOrt4HuJb3/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Azure Cognitive Search
Open Cascade and ask: "Using Azure Cognitive Search, help me...". 7 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"azure-cognitive-search": {
"url": "https://edge.vinkius.com/vk_preview_hdKYLP4Ky0e0ym1FqqZkykLxQEDMxyTOrt4HuJb3/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Azure Cognitive Search
Ask Cline: "Using Azure Cognitive Search, help me...". 7 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add azure-cognitive-search --transport http "https://edge.vinkius.com/vk_preview_hdKYLP4Ky0e0ym1FqqZkykLxQEDMxyTOrt4HuJb3/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Azure Cognitive Search
Ask Claude: "Using Azure Cognitive Search, show me...". 7 tools are ready
Where the request belongs
Work Azure Cognitive Search can move forward.
This is for the engineers and architects who are tired of switching tabs between the Azure portal and their code. It's for anyone managing high-scale enterprise search who needs to debug retrieval logic on the fly.
Search Architect
Testing BM25 parameters and vector similarities without writing custom scripts.
Data Engineer
Verifying that indexers are pulling data correctly from storage accounts.
MLOps Engineer
Comparing schema changes and testing retrieval techniques across different environments.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsAzure AI Search
Execute RAG queries against Azure AI Search natively. search vectors, full-text documents, and audit cloud indexes directly from your AI agent.
Elastic Enterprise Search
Manage enterprise search via Elastic. search engines and documents, handle indexing, and monitor search analytics directly from any AI agent.
LlamaIndex (AI Data Framework & RAG)
Query and manage RAG pipelines via LlamaIndex. execute natural language searches, audit indexed files, and monitor data pipelines.
Lucidworks Fusion (AI Search & Discovery)
Manage AI-powered search via Lucidworks Fusion. execute semantic queries, index documents, and monitor ML training jobs.
GroundX
Data search and RAG optimization platform.
Amazon Bedrock KB
Connect your AI agent to AWS Bedrock Knowledge Bases. execute semantic searches, managed RAG, and sync vector datasources natively.
Bring your own AI
Change the model, client or framework. Keep Azure Cognitive Search connected.
-
Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Azure Cognitive Search.
The practical details behind the request, access and result.
Can the Azure Cognitive Search MCP help me debug my data pipeline?
Yes. You can use it to check if your indexers are running successfully and see the latest status codes without leaving your chat window.
How does this Connector handle vector searches?
It allows your agent to perform K-Nearest Neighbor (KNN) searches against your existing embedding profiles in Azure.
Can I use this to see if my OCR skillsets are working?
Yes. You can list your active skillsets to confirm that cognitive services like OCR are correctly configured and active.
Is this Connector for searching general web results?
No, this Connector is specifically for querying your own enterprise data hosted on Azure Cognitive Search.
Can my AI agent find a specific document using a UUID?
Yes, it can pull the exact raw JSON for a single record if you provide its unique UUID key.
How do I check which indexers are currently active?
Your agent can list all scheduled indexers and report their current status, including any errors or success codes.
Can my AI use this connector to grab an individual document by its key?
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.
Does it also show Cognitive Service enrichment skillsets?
Yes. This connector tracks and lists structured Cognitive Skillsets. Your agent can discover whether OCR, translation features, or entity extraction bots are currently attached and applied correctly inside the Azure indexing pipeline.
Can it search using direct text inputs and semantic rankings?
Absolutely. Using the lexical search capability, your agent can push natural string keywords right into Azure. It returns mapped documents ranked gracefully using BM25 relevance or integrated semantic processing out of the box.
One connection away
Give your agent a direct line to Azure Cognitive Search.
Connect Azure Cognitive Search once. Keep it beside 5,900+ managed Connectors when the next task needs more.
Explore every Connector No credit card required · Free tier available