MCP Server Development and AI Agents for Small Business
Our MCP server development lets AI assistants such as Claude use your own CRM, database and internal tools, and we build AI agents that work through multi-step jobs on their own, even on a schedule. MCP (Model Context Protocol) is an open standard, introduced by Anthropic in November 2024, for connecting AI assistants to tools and data, and Claude, ChatGPT and many other tools support it.
- Free 20-minute consult
- Based in Tulsa, OK ยท working nationwide
- Plain English, no jargon
Who needs MCP server development or an AI agent?
Custom MCP servers and AI agents are for small and mid-sized businesses, roughly 2 to 200 employees, that want AI to work with their own data and systems. If your team keeps copying information between an AI chat and your software, or a repeat job eats hours every week, this is for you.
- Teams that want Claude or ChatGPT to look things up in their own CRM, database or files
- Businesses with document-heavy work, like pulling details out of PDFs and reports by hand
- Owners who want a recurring job, like a morning research brief, done on a schedule without anyone asking
- Teams tired of copying and pasting between an AI chat and the software they already use
Not every job needs an AI agent. If the steps never change, a regular workflow automation is often simpler, and we'll tell you if that's the case.
What's included in MCP server and AI agent development?
You get AI integration for your small business, built around the systems you already use: MCP servers that connect AI assistants to your data, AI agents that finish multi-step jobs and tools that turn documents into data. Every build starts with a written proposal and includes weekly or biweekly progress updates.
- Custom MCP servers that let Claude, and other assistants that support MCP, work with your CRM, database or internal tools
- LLM tool integration: giving an LLM (a large language model, the technology behind assistants like Claude and ChatGPT) a short list of actions it's allowed to take
- AI agent development for multi-step jobs, including scheduled agents that run on their own
- Document-to-data tools that read PDFs, such as court filings or property reports, and turn them into structured fields
- Multi-agent systems, where specialized agents each handle one stage and a final step checks the work
- A plain-English walk-through of what the AI can see and do, and the risks, before it goes live
How does an MCP server or AI agent project work?
Every project follows four steps (Discover, Design, Build and Deploy), and you stay in the loop the whole way. It starts with a free 20-minute call, and you'll know what the AI can see and do before it touches your live systems.
Discover
A free 20-minute consult, then a scoping conversation about the job you want done, the systems involved and what the AI should and shouldn't touch.
Design
We decide with you what the AI can see and do, then send a written proposal with a fixed price or a range.
Build
We ship a first version fast, then improve it with you, with weekly or biweekly progress updates.
Deploy
We connect it to your live systems. Hosting costs pass through to you, and ongoing support is available as a monthly plan.
What tools do we use to build MCP servers and AI agents?
We build MCP servers with the MCP SDK and FastMCP, and AI agents with Anthropic's Claude API and Claude Agent SDK, running on Node.js, Deno or Python.
- The MCP SDK and FastMCP, toolkits for building MCP servers
- The Claude API, the connection that lets software hand work to Claude
- The Claude Agent SDK, Anthropic's software development kit for agents that use tools and work through multi-step jobs
- Claude Code skills, saved instructions that teach Claude a specific task
- Node.js, Deno and Python, the programming environments the code runs on
- Supabase, a secure database for the records an agent writes
What is an MCP server used for?
An MCP server is used to let an AI assistant work with a system it can't otherwise reach, like your CRM, your database, a shared drive or an internal tool. Instead of copying and pasting between apps, your team asks Claude or ChatGPT a question, and the assistant uses the server's tools to find the answer or take the action.
A custom MCP server is built around your systems and the exact actions you want to allow. Because MCP is an open standard, the same server can work with Claude, ChatGPT and other assistants that support it, so you're not tied to one AI company.
- Look up a customer, an order or a job in your CRM and answer in plain English
- Search your own documents, so answers come from your information instead of the open web
- Pull figures from your database for a quick summary, without anyone exporting a spreadsheet
- Add or update a record, such as logging a call note, when you've allowed the AI to make that change
- Give the AI access to an internal tool your team already relies on
What's the difference between MCP and an API?
An API (application programming interface) is a set way for one program to talk to another, like a door into one system. MCP is a standard way for an AI assistant to use many doors: it describes each tool in plain words the AI can read, so the assistant knows what the tool does and when to use it.
The two work together. Many MCP servers call a system's API behind the scenes, and the MCP layer is what lets an AI assistant find that API's abilities and use them when you ask.
| Question | An API | An MCP server |
|---|---|---|
| Who uses it? | Programmers, who write code against it | AI assistants, when you ask them a question |
| Does every one work the same way? | No. Each system has its own rules and format | Yes. Every server follows the same open standard |
| How are its tools described? | In technical docs written for developers | In plain descriptions the AI reads to pick the right tool |
| Which AI assistants can use it? | None directly, unless someone writes code to connect them | Claude, ChatGPT and other assistants that support MCP |
| What's an example? | Your CRM's API lets software pull a contact record | An MCP server lets Claude look up that contact when you ask |
What can an AI agent do for a small business?
An AI agent can take a repeat, multi-step job off your team's plate: it follows the steps, uses only the tools it's allowed to use and hands you the result, even on a schedule. Here's what that looks like in the AI agents and document tools we've built.
- Scheduled agents that run on their own. Our daily AI intelligence brief is a Claude agent that scans AI news, docs and community sources every morning and writes a short brief on what changed and why it matters, with sources. It has run daily since March 2026.
- Document-to-data tools that read PDFs so people don't have to. One turns property-data report PDFs into structured fields for a real estate pricing analysis. In a nightly lead pipeline, Claude reads public court filing PDFs and pulls out the property details.
- Multi-agent systems that split a big job into stages. We built one on the Claude Agent SDK in which specialized subagents handle discovery, document gathering, web extraction, document analysis, regulatory checks and QA validation, then write validated records to a database, with daily automated audits.
- Helper agents for a specific project. For an app launch, we built Claude Code subagents that triage beta feedback, handle growth outreach and run a pre-release checklist that ends in a go/no-go call.
Are MCP servers secure?
An MCP server is as secure as the way it's built and the access it's given. The AI can only do what the server allows, so the safest setups give it the smallest set of data and actions the job needs, and keep a person in charge of anything that changes your records.
Good MCP security also means knowing where your data goes, because whatever an assistant reads through an MCP server is sent to that AI provider. Anthropic doesn't use data from Claude for Work (Team and Enterprise) or its API for model training by default, but chats on its consumer Free, Pro and Max plans may be used unless you opt out. OpenAI says data from ChatGPT Business, Enterprise and Edu and its API isn't used for training by default. Check which plan your team is on before you connect anything.
We're honest about risk. We'll walk you through what the AI can see, what it can do and what could go wrong, in plain English, before it touches your live systems.
- Start read-only. Let the AI look things up before you let it add, change or delete anything.
- Give it the least access that does the job: only the systems, records and actions the task needs.
- Keep logins and access keys on the server, never pasted into a chat.
- Require a person's approval before any action that sends, changes or deletes something, and keep a log of what the AI did.
- Treat outside content with care. Emails, web pages and files can hide instructions meant to trick an AI, so an agent that reads them shouldn't be able to act on them unchecked.
- Only install MCP servers from sources you trust, the same as any other software.
MCP server and AI agent questions
What is an MCP server, in simple terms?
An MCP server is a small program that gives an AI assistant a set of tools it can use in one of your systems, such as looking up a customer, searching files or adding a record. MCP stands for Model Context Protocol, an open standard for connecting AI assistants to tools and data, so the same server can work with Claude, ChatGPT and other assistants that support it.
Is MCP still relevant in 2026, now that Claude has skills?
Yes, because MCP and skills do different jobs. A Claude skill is a folder of instructions that teaches Claude how to do a task. An MCP server gives an assistant access to a system, like your CRM. Claude plugins can bundle both. And since MCP is an open standard that Claude, ChatGPT and many other tools support, a server you build isn't tied to one AI company.
Learn about custom Claude skills and pluginsWhat is an AI agent, and how is it different from a chatbot?
An AI agent is an AI system that works through a multi-step job on its own, using tools along the way, while a chatbot answers questions in a conversation. A chatbot waits for someone to type. An agent can start on a schedule: our daily AI intelligence brief is a Claude agent that scans AI news, docs and community sources every morning and writes a short summary with sources.
Learn about custom AI chatbots for small businessCan Claude or ChatGPT connect to our CRM or database?
Yes, through an MCP server. Claude, ChatGPT and many other AI tools support MCP, so a custom MCP server can let them work with your CRM or database, limited to the actions you choose, such as read-only lookups. Your team can then ask questions in plain English and get answers from your own data. Whether it fits your setup depends on the systems you use, which we can check on a free consult.
See how we set up Claude for teamsHow much does an MCP server or AI agent cost?
We don't publish prices, because cost depends on scope: how many systems it connects to, how many actions it needs and whether it runs on a schedule. After a free 20-minute consult and a scoping conversation, you get a written proposal with a fixed price or a range. Payments follow milestones, starting with a deposit. Hosting costs pass through to you, and any scope change needs a written change order, so there's never a surprise invoice.
Read how our pricing worksWill an AI agent replace my staff?
That's not what we build them for. We use AI agents to add capacity rather than cut people. An agent takes a repeat job off your team's plate, like reading stacks of PDFs or checking sources every morning, so your people can spend that time on work that needs them. You decide what the agent does and what stays with your team.
Do I need to be technical to use an MCP server or AI agent?
No. Once an MCP server is connected, your team uses it by asking the AI assistant questions in plain English, the same way they'd chat with Claude or ChatGPT. A scheduled agent needs even less: it runs on its own and delivers the result. The technical work is on our side, and we explain what the AI can see and do before it goes live.
Have another question? Our AI consulting FAQ covers cost, timelines, data privacy and ongoing support, or you can ask us directly.
Want AI that works with your own systems?
Book a free 20-minute consult. Tell us which systems and which job you have in mind, and we'll tell you honestly whether an MCP server, an AI agent or something simpler is the right fit.
Prefer email? Write to admin@legacyaisolutions.ai.