Tag: Redgate Monitor

I have been experimenting with MCP servers in a few ways, including the Redgate Monitor MCP Server. It took me a few tries, and some help from engineers to get connected. I’ll cover how I did this in Claude and Visual Studio Code in this post, and try to warn you about a few places I made mistakes.

This is part of a series of posts on Redgate Monitor. Click to see the other posts.

Creating A Token

I’m not going to bore you with the setup and configuration of the Redgate Monitor instance. That procedure might change by release, so I’ll assume you’ve got the MCP server enabled.

To access the MCP server, you need to give your AI agent a token. This authorizes the MCP server to connect to Redgate Monitor and read data. These are read only tokens, and designed for the MCP and the tools that are available.

In the configuration, there is an Access Tokens area. Click here.

Click Create Token on the next screen. This is in the upper right.

On the next screen, give your token a name, description, and set an expiration date. The default is one year.

Make sure you select the MCP type. I messed this up the first time.

Below this, pick the servers the MCP token can access. I’ve selected just the Production serer group, but you can set this as needed. I’d make sure the name and/or description lets you know what can be accessed.

You will get a review screen, to verify what you’ve done. Accept that and you’ll get a dialog with the token value. Make sure you save this securely somewhere.

Once you’ve created this, it’s in a list, and you can click the “view details, which shows you what the token can access, as you can see below. You cannot get the token itself anymore.

Configuring VS Code

I’m going to show this working in VS Code. I opened the Command Palette and selected the MCP: Open User Configuration, as shown.

Inside the config, I pasted this inside the “servers” key. This should be a sub element, and this goes alongside any other MCP servers.:

"redgate-monitor": {
  
 "type": "http",
  
 "url": "https://<your-monitor-host>/mcp",

 "headers": {
  
 "Authorization": "Bearer ${input:redgate-mcp-token}"

 }

 }

Then inside the “inputs” key, add this:

{

 "id": "redgate-mcp-token",

 "type": "promptString",

 "description": "Redgate Monitor MCP token",

 "password": true

 }

The save this. When you start the MCP server, it will ask you for your token. Paste the value in and then you should connect. You do this from the MCP: List Servers item in the command palette. This should give you output like this, with a connection message and tools discovered:

If I open a chat, and add the MCP as a tool, I can ask questions. Here’s a question I asked and the initial responses from the LLM.

 

Once this is done, I’ll get a list of the alerts. I did approve some PoSh commands where the LLM stored results from Redgate monitor and then tried to process those after writing them to a temp file.

\

This is the raw LLM trying to use tools and fumbling around. With a few skills and guidance, this will run smoother, quicker, and more efficiently in your environment.

Summary

The Redgate Monitor MCP server is a great way to start using AI to analyze all the data in your database estate that Redgate Monitor collects. There were 7 tools when I started, but within a few weeks there were 11. By the time you read this, there are likely going to be even more.

Give Redgate Monitor a try and learn how to use MCP servers to link your LLM to Redgate Monitor and start analyzing systems in a more natural manner.

Redgate Monitor is a world-class monitoring solution for your database estate. Download a trial today and see how it can help you manage your estate more efficiently.

I have been experimenting with MCP servers in a few ways, and pressing on our Redgate Monitor team to add one to their system. They did, started adding tools, and are continuing to work. I’m excited.

Here’s a quick look at the MCP server for Redgate Monitor (preview in July 2026).

This is part of a series of posts on Redgate Monitor. Click to see the other posts.

Getting Started

I’m not going to bore you with the setup and configuration. You do need to be on a 14.23 or later as the version. Your account rep can get you setup instructions, which are still be worked on and finalized. This is really a work in progress as of this writing (Jul 30) and I’ve found a few things that didn’t quite make sense, so be patient. This is editing the Monitor Webserver config file and enabling this.

Once that’s done, it’s a little tricky with an AI agent system. This is the high level, and I’ll do some more detailed notes about getting this in VSCode and Claude, where I work. The basic steps are:

• Enable in Redgate Monitor
• Create an MCP Access token
• Add the MCP config to your Agent setup

It’s not quite as simple as it sounded to me, but it wasn’t that hard. It’s mostly working through some of the steps and ensuring you get your JSON correct.

Accessing the MCP Server

I connected with Claude for the demo in the Video Walkthrough below, but I’ll give you a quick look here. I set my token for the prod/staging/dev systems. When I look at the test instance of Redgate Monitor, I see this: lots of servers and alerts.

Once the MCP server is added, I start Claude and run a /mcp. I see my server get connected.

There are a number of tools, which have grown since I started testing. I don’t have a complete list and anything I put here will be out of date in a week, so I won’t bother. In any case, I’ll ask for the production servers. I can see the various base monitors being queried. This is slower than almost any customer, since we have more BMs than most people here. Most have 1-2 at most.

Note: I did get asked for permission a few times before the tools were accessed. Since all MCP stuff is read-only now, I just granted permission for all sessions.

Here are the results. Note the summary at the bottom.

I next asked this: which servers are in critical status and why. The Claude LLM interprets this and starts querying the Redgate Monitor server, using the token for security, and the tools, which are really the API of things that can be run.

The results I got were what you see below. The LLM had to run a bunch of queries to get results and the read in those results and interpret them. In this case, there were a lot of different queries of tools to look for data. This probably took a minute or two, but it feels long while watching the screen.

I next asked about queries on an instance. I don’t know these servers that well, but I know there are workloads on some to simulate what clients see. I decided to ask about one of the 2019 instances in production. In this case, I got asked for permission for a new tool (I hadn’t run the top queries tool) and then the agent went to work. You can see the tool usage and results. In this case, the system was down when I ran this, and it let me know this was from before the outage.

At the bottom, there are some observations, which can be useful. I’ve got cursors running, XEvents, etc. Helpful to look at this for a system I don’t spend a lot of time examining.

Ultimately the MCP server is a way for you to use tools you use already, but allow them to query the data in Redgate Monitor.

I’m excited to see where this can go, and how it can help customers interpret all the data collected by Redgate Monitor and more easily summarize it. This will be useful to some, though others of you might not like MCP access and instead stick with the internal AI tools.

It’s up to you, but we are giving you the choice to work as you wish.

Summary

The Redgate Monitor MCP server is in preview as of July 2026. I tried to give you a short sense of how you can use this to query Redgate Monitor and keep an eye on your systems. There are lots of ways to work, and I’ll try to give some guidance on specific things over time, but for now this gives you a sense of how MCP works.

I’ll do future posts that cover the config and help you get testing in your own environment.

Redgate Monitor continues to grow and advance and MCP capabilities are a great way to start using AI to help manage a large database estate, with your own AI resources.

Redgate Monitor is a world-class monitoring solution for your database estate. Download a trial today and see how it can help you manage your estate more efficiently.

Video Walkthrough

Watch me use the MCP server live.

We keep adding new AI capabilities to Redgate Monitor, where it makes sense. Check out this new feature we’ve added for alerts. This is a great addition to help a busy Ops staff cope with a large database estate.

This is part of a series of posts on Redgate Monitor. Click to see the other posts.

Alert Index Analysis

One of the new things we’ve added in Redgate Monitor is an AI analysis of your alerts. This isn’t for every alert. Right now, we have three where this works in preview:

• Long-running query
• blocking process
• Deadlock

This is documented on its own page.

You can see this if you go to the Alerts page and look for a blocking process alert. Here’s a URL, but this repeats regularly, so just find the alert. You should see something like this:

If you click on the alert, then you’ll see the details, as shown here. However, to the right is an “AI Analyze Alert” button.

If you click that, a blade slides out from the right, and it has some analysis in it. This has a summary at the top. For my session, this had ended, so the summary is nice in that it gives me an overview with the time of the blocking and the statement. There is also a root cause analysis below this. This is something that would help me quickly answer questions from my boss.

Further down there is a diagnostic review, which helps you navigate Redgate Monitor to verify things. You should use the AI to help you and still verify what it says. This is a good explanation, but worth double checking. There are also recommended actions below this.

It’s a good way to approach a series of alerts, especially in a busy environment where you might have lots of these alerts across different systems.

Summary

AI is a great tool in places, and this is one of those measured approaches from Redgate to use AI where it’s helpful and useful, and does some work for you. Looking across a bunch of similar data and getting patterns, getting some quick insight into timings, that’s useful. This might be especially great when someone calls you with a question and you need a summary.

As always, you should verify the diagnosis and recommendations before you do something, but this does give you a quick place to start fixing chronic issues in your system. I look forward to AI analysis coming to other alerts.

Redgate Monitor is a world-class monitoring solution for your database estate. Download a trial today and see how it can help you manage your estate more efficiently.