smplkit MCP server

This is a helper that connects your AI assistant to smplkit, a service for controlling how your apps behave in different environments. Once it is set up, you can ask your AI in plain words to flip a feature flag, change a setting, or schedule a job, and it will do it for you. It is handy for developers and anyone who runs software and wants to make changes without clicking around a dashboard.

What this MCP server does

You ask your AI something like turn on the new checkout for enterprise users in production. The AI uses this helper, which talks to the smplkit platform on your behalf. smplkit makes the change, and the helper sends the result back to your AI. Your AI then tells you what happened and can answer follow-up questions using the live state. It can also schedule jobs, change log levels, and search audit events the same way.

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What you can do with it

• Turn feature flags on or off for specific environments and user groups
• Change configuration values like database hosts for staging or production
• Raise or lower log levels to debug an issue, then reset them
• Search the audit log and set up forwarders to send events to tools like Datadog
• Create scheduled jobs that call a web address on a cron schedule or once at a set time
• Run a job right away to prove it works and see the response
• List your environments so you know which ones you can target

Try asking your AI

• “Create a boolean flag called new-checkout, off by default, then turn it on in prod only for enterprise users.”
• “List my environments, then set database.host to db-staging.internal for staging.”
• “Raise the sqlalchemy.engine logger to DEBUG in production while I debug, then reset it.”
• “POST https://api.example.com/cache/warm every morning at 7am New York time, then run it now to prove it works.”

What it gives back to you

You get answers in the chat, like a confirmation that a flag is now on, a list of environments, or the response a job got when it ran. It can also show you audit events or the current value of a setting. Everything comes back as plain text you can read and act on.

Before you start

Who it's for

Developers, DevOps engineers, and anyone who manages feature flags, configs, or scheduled jobs and wants to do it from chat.