Voice of the DBA

Tag: AI

Monday Monitor Tips: Configuring Access to the MCP Server
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.
August 24, 2026
The New World Of AI Robots

It’s been a good time for robots. While on vacation last week I caught this video of a robot running. It’s impressive for a bit, and then it devolves into the inspiration for lots humorous comments as it crashes into a wall. There are some funny comments, but some pedantic ones that note the robot can’t beat a human record because it’s not a human.

That’s correct, but …

The comments miss the point. The robot will improve it’s capabilities, and much faster than a human can. The AI/ML advances of the last few years mean that we don’t have to program robots to be precise and exact. The fact that a robot can balance and run and stay inside the lanes is incredible. I suspect these robots, both humanoid and other form factors will start to become more commonplace in our world.

Which is scary.

Not for us tech people, though certainly AI advances are worrisome. More, I worry about other jobs. Think about the industrial robots of the last 30 years that have been used in places like car manufacturing. They are bespoke, designed to do certain jobs, and in a certain way. They are programmed with fairly tight tolerances to perform a specific task, often at a quicker and more reliable (and repeatable) way than a human can. There were plenty of false starts here, but today many robots are used alongside humans to assemble cars. You can see them working here, doing tasks that would be slower and harder for humans, even with mechanical aids.

There is talk of humanoid robots being used in place of some humans, reducing the slow and complex setup . This also lets the robots work in the same places and spaces, moving the same way, as humans do. This might reduce some of the labor costs in the future. That might not seem like a big change overall, as lots of manufacturing uses automation in some way today, but think past this.

You can purchase a humanoid robot for under $5000. That might not be very capable now, but as LLMs get more capable and perhaps specialized models for different purposes like image recognition, this is an issue. Imagine you own an oil change business. You pay 5 people to do most of the work on cars. Those people likely cost you $2000-2500 a month each. That’s the cost of 2 robots, without the hassles of hiring, termination, breaks, etc. An AI LLM can already identify items from a camera image. Is it a far stretch to think that a robot could identify the oil drain plug and the oil filter on a car by moving around it? How hard would it be for a robot to grab a human ratchet, pick the right socket after a database lookup, and remove the plug. They could tell when the oil finished draining and then replace the plug, tightening it to the correct torque. And being a robot, they might do this without forgetting to position the drain or replace the plug.

In my mind, a $5k robot quickly becomes capable of a lot of human jobs. There might still be the need for some humans, but we might easily replace 50%+ of them in a lot of common jobs. Stocking shelves, acting as cashiers, who knows what else these AI driven systems might accomplish. That’s truly a scary world, where human labor in many cases might be devalued.

In the software world, it seems the people having the most success have the best judgment. People who are above average software engineers get above average results from LLMs, and I suspect this will be the case for a long time. Very average, or worse, engineers get worse results and I think are the source of many of the stories of AI coding failures.

I don’t know what a lot of manual labor jobs will do when management starts to experiment with robots, but I know that in our world you can compete and succeed against AI coding agents by learning to work with them, apply your judgment and use them as tools that make you more effective.

Steve Jones

August 22, 2026
Don’t Fight with AI

I was recently trying to handle a simple task with a few AI tools to see how well things worked. I realized that AI isn’t great for everything and there are times you need your judgment to stop fighting AI and use other tools.

Tl;dr choose the shortest path and know your tools. In this case, just copy paste a script and results (see the bottom).

This is part of a series of experiments with AI systems.

The Scenario

I have a table with some data. I wanted to duplicate this table DDL and DML for another system. Here’s my table:

Simple thing, right? Lots of possible ways to do this, but understand, this wasn’t the task. I was doing something else, with another goal.

This task was just in my way.

First Try – Prompt AI

I use SQL Prompt all the time, so I thought, hey, AI, script this.

Well, not quite what I wanted. This works cross database, or if I make a new table name by editing the script in two places. But not ideal.

OK, I asked for the data, and this works. A bit. I only get 10 rows. To be fair, the original select I started with was top 10.

I then ask for the other data, and I go backwards. I don’t know why a model would go in this way. This reminds me of working with a junior person half listening to me.

Grrrr.

Claude CoWork

This seems like a cowork task. I’m not saying this is the best thing, and since I didn’t have a repo, I decided this over code. In any case, I asked for a task. Quickly Claude gave me options for 1) PoSh, 2)T-SQL, 3) something else. I picked 2 and it took about 4 minutes or so, but I got this script.

I had to open in VSCode, connect to SQL, and then it didn’t work:

Paste back into Claude, get a quick fix, maybe 15s.

Copy/paste the script, which runs. Certainly I could have put this back in SSMS, but I’m not sure that’s easier/harder.

I copy the results, which is fairly easy here.

I have the script I need and can move on:

Redgate Assistant

We’ve added a new Redgate Assistant panel to SQL Prompt. I tried this next, and got a few results. The DDL was first, which I could copy/paste into my new query window.

The second was a script I pasted in and ran, which gave me insert statements. Taking these results gives me about what I have above from the Claude script.

This was significantly faster. From prompt to result was in the 10s range and then I could get the results in a few more seconds. That’s quick, and I didn’t lose my thought context.

The Best Way – SQL Prompt

I’m experimenting with, and it’s been a tool I reach for often, but as I was annoyed by Claude taking so long, I realized the best way was actually this. Run the query in SQL Prompt that’s at the top. Then select all the data in the results by clicking the top left box and right click. Select “script as insert”.

I can then easily search/replace or edit the name of the table.

Doing this, once I thought about it, was about 5 seconds of effort, no context switch. Just grab this, change the name and go on with my other work on another connection.

Use All the Tools

I do think AI is a great tool for me. I also think it can cause me to spend more time and effort (and sometimes $$$) on simple tasks. While I’m all for experimenting, I also want to be efficient and effective.

Fortunately, I’m somewhat paid to try different things and report on them.

In this case, the KISS solution is best. Use Prompt what what it does best, work with your schema, code, and (lightly) data. I know I could use an MCP server, or Claude Code at al with more guidance, or something else, but those start to feel like using AI for the sake of AI and burning tokens when there are better tools.

Not everything is better with AI. The people who succeed and prosper in this crazy AI world will embrace it when it’s most helpful and ignore it when it’s not very useful.

August 10, 2026
The Quiet Part

Apparently, Meta did what a lot of employees suspect their management will do: use AI to lay off people. In this case, there is a report (and lawsuit) that Meta used it’s AI-integrated HR platform to make decisions about who to let go in a layoff. The rumor is that the AI used productivity metrics to choose who was the target of the layoff. As with a lot of AI failures, this appears to be another case of poor communication guiding the AI, or the AI not actually taking individual situations into account.

A number of the people terminated were on maternity/paternity leave, which is a protected activity. Others may have been on other medical leave, though for privacy reasons, the article doesn’t have firm data to prove this. The lawsuit will likely bring more of this out, but this appears to be a case not just of AI making decisions, but of poor behavior from management. Plaintiffs were discouraged from taking leave off, which is something sh****y humans have said to people for decades. We need you; your baby or family isn’t important, so don’t use your leave. It’s one aspect of working in the US that is way worse than overseas, where there are more employee protections.

Meta disputes the case, saying the AI didn’t make decisions. However, that brings out an interesting point. If the AI recommends things, who’s responsible? The humans, right? They still have to sign off on the decision. If they don’t perform due diligence, they’re still responsible, correct? I think so; after all, I’m responsible for code the AI writes if I commit it. Even if an agent does the work, I have to oversee it and approve (or grant permissions for) the actions.

I. Am. Responsible.

Trusting an AI to do a lot of work is like trusting a lot of smart, but very inexperienced staffers to work in your environment. There are always inconsistencies and reasons why we might code something, configure something, or deploy something a certain way. What seems like a good way to tackle the situation from the outside doesn’t always make sense when you have experience. Humans often have experience that AI agents lack.

LLMs are relatively stateless, and while we can provide context, give them guidance, and provide comprehensive codebases, they still sometimes do silly things. This can be problematic, especially with database changes, which are stateful and disruptive to rollback.

AI agents can make mistakes much like humans, only faster. Much, much faster.

Labor is one of the most expensive parts of many organizations’ budgets. Plenty of management would like to replace relatively expensive humans with cheaper tokens. That isn’t working out as well in practice, despite lots of experiments. Hopefully, other organizations realize that AI is a tool, not a replacement for humans, and we can’t trust it or even believe it’s outputs without some human judgment.

Steve Jones

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August 7, 2026