The Standard For Connecting To AI
When Claude reads a file out of Google Drive or ChatGPT checks a calendar, under the hood, an MCP server is doing the work. MCP (Model Context Protocol) is the open standard that lets an AI assistant securely use outside tools and data, and it works the same whether the tool is Google Drive or the software your business runs on.
The catalog of off-the-shelf connectors already covers the SaaS tools ingrained in your everyday work.
Microsoft 365, Google Workspace, Slack, Figma, Atlassian, etc.
But it doesn't yet connect to your database, your API, or your proprietary knowledge that makes your business valuable.
That's the connection we build for you. Custom MCP servers that make your systems as available to AI-powered clients like ChatGPT, Claude and Copilot.
What It Solves
Your users are drifting away from your traditional web and mobile applications and towards AI-native applications like ChatGPT instead.
An MCP server puts your product inside ChatGPT and Claude, so people can use it from the chat window they already have open.
You want to sell to agents.
An MCP server for your business lets agents discover, browse and purchase your services.
Customers ask ChatGPT about your product and it gets it wrong.
With an MCP server, ChatGPT can answer from your live product data instead of guessing from whatever it found on the web.
You want your app listed in the Claude and ChatGPT directories.
We build the server to the directories' requirements, authentication included, and see the listing through.
Your team lives in Claude, but your data is stuck in the tools you already pay for.
A custom connector lets Claude read from and write to the tools your team already uses, so the work happens in one place.
AI can't reliably use or access your backend services.
We adapt and extend your existing services so they integrate with AI clients.
What It Gets You
Customers who can get things done with you from inside ChatGPT or Claude.
We connect the server to the systems behind your product, so the assistant can finish the task for the customer instead of sending them to your site.
A presence in the AI assistants your customers already use.
If your server is live when someone asks an assistant for a service like yours, it can send them to you.
Usage data from the places your customers are spending more and more of their time.
You see what people ask assistants to do with your product and where those requests fall short, which points to what to build next.
A new channel for your product to grow into.
Access from ChatGPT and Claude can be packaged however suits your business, as part of an existing plan or as an offering of its own.
What a Custom MCP Server Can Do
An MCP server makes your service or application available to AI natively.
What you do with this integration is up to you.
Some clients want their team working with AI that can see inside the business. Some want their business reachable by their customers' AI assistants. Some want the whole picture. It's the same standard either way.
For Your Team
Your business data and tools, available inside the Claude or ChatGPT your team already uses. Ask a question, get an answer drawn from your own systems. And once your tools speak MCP, AI agents can run whole workflows against them, with a person approving the output.
- A custom connector to your CRM, database, or scheduling software
- Auth and permission scoping, so who can see what stays your call
- Installed on your team's seats, with a short walkthrough
- Agent workflows with human-review gates and full logging, when you're ready for them
- Hosted and monitored by us, or handed off to run on your infrastructure
For Your Customers
Customers increasingly ask their AI assistant first. A customer-facing MCP server makes your product or service something an assistant can find, understand, and act on.
- A public MCP server with a catalog of what you offer
- Tools that allow AI to use your service in a secure, AI-native fashion
- Discovery metadata, so assistants can find you on their own
- Logging, so you see which agents showed up and what they asked
How It Works
Step 1: Map
A working session on where AI should plug into your business: which data it needs to see, which tools it should be able to use, what your customers' assistants should be able to do, and what nothing is allowed to touch.
Step 2: Build
We build and test the server against your service.
Step 3: Deploy
We deploy and host the server on your infrastructure or ours.
Step 4: Ship
- Publish your MCP Server to the connector directories.
- Register your MCP server with MCP Registries.
- Connect it to your internal systems.
Step 5: Extend
When you want more, we add it to the same server: new tools, agent workflows, or the other direction (public if you started internal, and vice versa).
Who It's For
Spreadsheet-Run Businesses
You run the company from spreadsheets and want Claude to just read them.
Sales Teams
Call prep and pipeline questions answered straight from the CRM, in the assistant reps already use.
SaaS & Product Companies
Sign-ups, demos, and support reachable by your customers' AI assistants.
Startup Founders
A product that AI agents can find and use while that's still rare in your market.
Ops Managers
Weekly reporting assembled by hand from tools that don't talk to each other.
Leaders Worried About Leaks
You want the team using AI on real work and you want customer data to stay inside your systems. Both, with permissions you control.
Start With a Free Hour
Tell us which of your systems you wish your AI tools could see, or what you'd want a customer's assistant to be able to do. In an hour we can usually tell you what the server looks like, what it would cost, and whether it's worth building.
Book a Free Consult