Is this MCP secure? Does it give global access?

No. Security is the core feature. The MCP strips away global Azure permissions. It locks the agent down to query only one specific Log Analytics table, preventing access to sensitive global audit trails.

What language does it support for querying?

It supports full Kusto Query Language (KQL) syntax. This means you can use advanced functions like filtering, parsing JSON, and time-based operations.

Do I need to specify the table name in my prompt?

No. You don't. The engine automatically prepends the authorized table name to your query. You only need to provide the KQL operations themselves.

Can I use this for general monitoring?

Yes, but it's highly focused. It's designed for deep, scoped observability, allowing you to troubleshoot specific application errors or analyze traffic spikes within the defined table.

What kind of data can I retrieve?

You can retrieve structured data like error codes, user IDs, timestamps, and parsed JSON payloads, provided that data exists within the configured Log Analytics table.

Why limit the agent to a single Log Table?

To enforce zero-trust security. A Workspace often contains sensitive audit trails (like AzureActivity or SecurityEvents). By locking the agent to a specific table (e.g., 'AppExceptions'), you prevent it from reading global infrastructure access logs.

How should I format my KQL queries?

You do NOT need to include the table name. The MCP engine automatically handles the table prefix. Just pass the KQL operators starting with a pipe. Example: | where TimeGenerated > ago(1h) | limit 50.

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Connect Azure Log Analytics Workspace to ChatGPT and Claude

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Debug production issues without global access risks.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 1 capability

We ship only the actions that matter.

Capability set01 / 01

01

1 capability in this set.

Part of 1 available through Azure Log Analytics Workspace.

01
Query logs
Execute a Kusto (KQL) query against the configured Log Analytics table. You only need to provide the KQL operations (e.g., | where TimeGenerated > ago(1h) | limit 10); the engine handles prepending the authorized table name.

Real work

What teams actually run

Investigating a Service Outage

A service went down at 2 PM. You ask the AI to query logs for all 'Error' severity entries between 1:55 PM and 2:05 PM to pinpoint the failure point.

Auditing User Access

You need to know if a specific user accessed a resource yesterday. The AI filters the logs by the user ID and the date range to confirm the activity.

Analyzing Performance Degradation

The system is running slowly. You ask the AI to count requests per minute over the last two hours to spot a clear pattern of resource exhaustion.

Debugging API Calls

A client reports a failed API call. You provide the timestamp and let the AI query the logs to find the exact request payload and the failure reason.

Automate a task

Put Azure Log Analytics Workspace to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Azure Log Analytics Workspace works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

Building your own app? The connector is yours to use.

You don't need a client to put Azure Log Analytics Workspace to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

944ms average. Fast in production.

Azure Log Analytics Workspace is checked daily against the live service.

Daily averagePeak 1090ms

Oct 3Today

Fastest day: 724ms
Slowest day: 1090ms
14-day trend: Slowing+5%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 1 capability arrives ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Azure Log Analytics Workspace, so you can see the experience inside your AI.

It does not authenticate your account with Azure Log Analytics Workspace. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Azure Log Analytics Workspace Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_h8mzxcilFYlijQMfr5u3GIGk82xs7W4r1G5Um6EK/mcp

Claude Desktop

Follow the steps below to connect in seconds.

1In Claude Desktop, open Settings → Connectors.
2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3Click Add and start a new chat — Azure Log Analytics Workspace capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "azure-log-analytics-workspace-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_h8mzxcilFYlijQMfr5u3GIGk82xs7W4r1G5Um6EK/mcp"
    }
  }
}

Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Azure Log Analytics Workspace in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Azure Log Analytics Workspace owners hand off.

This MCP is essential for anyone who needs deep visibility into cloud infrastructure without the risk of over-permissioning. It's built for technical roles that need to debug systems quickly and safely. You'll use it when you need to prove a bug exists or understand why a service degraded.

01
DevOps Engineer
Use it to check application health and diagnose deployment failures by querying specific log tables.
02
SRE (Site Reliability Engineer)
It lets you analyze traffic spikes and performance degradation patterns without needing global access.
03
Security Analyst
You can monitor specific user behavior or access attempts within a controlled, limited scope.

FAQ

Questions Azure Log Analytics Workspace owners ask.

01
Is this MCP secure? Does it give global access?
No. Security is the core feature. The MCP strips away global Azure permissions. It locks the agent down to query only one specific Log Analytics table, preventing access to sensitive global audit trails.
02
What language does it support for querying?
It supports full Kusto Query Language (KQL) syntax. This means you can use advanced functions like filtering, parsing JSON, and time-based operations.
03
Do I need to specify the table name in my prompt?
No. You don't. The engine automatically prepends the authorized table name to your query. You only need to provide the KQL operations themselves.
04
Can I use this for general monitoring?
Yes, but it's highly focused. It's designed for deep, scoped observability, allowing you to troubleshoot specific application errors or analyze traffic spikes within the defined table.
05
What kind of data can I retrieve?
You can retrieve structured data like error codes, user IDs, timestamps, and parsed JSON payloads, provided that data exists within the configured Log Analytics table.
06
Why limit the agent to a single Log Table?
To enforce zero-trust security. A Workspace often contains sensitive audit trails (like AzureActivity or SecurityEvents). By locking the agent to a specific table (e.g., 'AppExceptions'), you prevent it from reading global infrastructure access logs.
07
How should I format my KQL queries?
You do NOT need to include the table name. The MCP engine automatically handles the table prefix. Just pass the KQL operators starting with a pipe. Example: | where TimeGenerated > ago(1h) | limit 50.