A scoped workflow
Choose a task and a representative set of examples. Identify the systems, data, and permissions required, and decide whether AI adds value or an ordinary automation would do the job.
AI integrations and automation
Give your agent a useful job and the tools to do it.
MCP, WebMCP, and automations that connect existing business tools.
Based in Columbus, Ohio. Available for remote projects.
01
Where I can help
An AI integration becomes useful when it can act on the right information inside an actual workflow. That could mean retrieving context from an internal system, preparing a draft for review, or helping a customer use a feature in your application.
I start with the task and the boundary around it: what the agent can read, what it can change, and what a person needs to approve. Then I build the connection and test the result against examples that matter to your team.
02
What we can build together
Tools connected to your application
Build MCP tools for direct service access, WebMCP tools for shared browser workflows, or integrations with your existing APIs. Keep validation and business rules in the application.
Boundaries and verification
Test correct completion, failure cases, retries, and human review. Document the supported clients, access setup, operating costs where measurable, and how to maintain the integration.
04
How we'd work together
- 01
Choose a measurable task
Define a correct result and record the current process. Agree on the tools and data the agent may access, including where a person reviews the output.
- 02
Build a small pilot
Implement the integration around existing application logic. Exercise useful examples, incorrect inputs, interrupted work, and permission boundaries.
- 03
Decide with evidence
Compare completion, time, and human corrections against the baseline. Expand the integration only when the pilot gives us a reason to do so.
The first conversation defines the fit. Scope, price, and timing are agreed before work begins.
Questions
Do I need MCP, WebMCP, or a normal API integration?
That is part of the assessment. A shared browser workflow is different from a background process. We choose the interface based on where the work happens and which clients need to use it.
Can an agent send messages or change records?
Only within the permissions and behavior we explicitly design. Read access, draft preparation, and final submission are separate decisions. Consequential actions need an appropriate review and authorization path.
Can we use the AI tools we already have?
Often. The pilot names the actual clients, models, and environments to support. We verify their capabilities and data handling before deciding how to connect them.
Start a conversation
Tell me what you need to make work.
These details give me enough context to suggest a useful first step.
- The task you want to automate or assist
- The applications and agent tools you already use
- The information involved and what must remain under human review
jeff@hooton.codes