Your Custom App Was Not on the AI's Training Data. We Fix That.
Every business has at least one application that runs the heart of the operation and that no off-the-shelf AI has ever heard of. Built in-house, bought from a niche vendor, customized beyond recognition. A line-of-business MCP server teaches your AI assistant how to read it, write to it carefully, and respect its rules.
A Bridge Built Around Your App, Not the Other Way Around.
Most AI assistants are general-purpose. They understand Outlook and Salesforce because the whole industry does. Your scheduling tool, your in-house operations console, your inherited Access database with twenty years of business logic, the vendor portal you live in every day, those are invisible. For line-of-business apps, custom is usually the answer, but not always. Some niche vendors are starting to ship first-party MCP servers, and community efforts cover a handful more. We check first, then build only what needs building. Whatever we build, the connector exposes exactly the parts of the application you want exposed, and nothing else. Read access where it helps. Write access where it is safe. Approval gates where it matters. Audit trail throughout.
Native and Public Options Are Rare Here. Custom Is Usually the Answer.
For a system the rest of the market does not know about, custom is most often the answer. But not always. Before we propose a build, we look at what the vendor publishes (a small but growing number of niche-platform vendors are shipping native MCP servers), what the community has built (rarely substantial for truly custom apps), and what your stack already supports. We propose the lightest path that fits, and build only when nothing off the shelf does.
- Native first, when it exists. Some niche-platform vendors are now shipping first-party MCP servers. When yours has, and it meets your governance, we use it.
- Public, in the rare cases it applies. If a community connector exists for your stack and is well-maintained, we evaluate it: read the code, pin the version, sandbox it inside your environment.
- Custom, when nothing fits (the common answer here). We learn your app first: the data model, the workflows, the constraints, the things people do not write down. Then we build the connector with explicit action allowlists, versioned and reversible write operations, and full audit.
- The same team builds and runs it. No generalist developer who leaves when the project ships. We document, monitor, and maintain the connector the same way we run the rest of your environment.
Where the Hours Come Back
Read From the System People Hate Opening
A legacy operations console that is slow and clunky. The AI assistant reads from it, surfaces the data your team needs, and they never open the UI for routine lookups.
Draft Updates the Operator Approves
A field tech radios in a status update. The assistant drafts the entry, the dispatcher approves with one click, the job record is updated cleanly.
Run Multi-Step Workflows
Booking a job, opening a ticket, scheduling a technician, sending the customer confirmation, and updating the project plan, all of which today require touching three or four applications. The MCP server orchestrates the steps; the human approves the critical ones.
Surface the Right Record Across Systems
A customer calls. The assistant pulls the matching record in your custom CRM, the open ticket in your support tool, the recent invoice in accounting, and the relevant document in your DMS, in one motion.
Expose Reporting That Was Trapped
A 20-year-old Access database holding two decades of operational data. The assistant queries it on demand and surfaces answers your team has been guessing at for years.
Replace the Twelve-Step Internal Manual
The kind of process new hires get a printed manual for. The assistant runs through the steps with the user, prompts for the inputs at each step, and posts the results to the right places.
What We Build For
We have built MCP servers, and the connectors that preceded them, against the kinds of systems off-the-shelf AI ignores:
- Custom web applications with REST or GraphQL APIs
- Internal tools built in PowerApps, Retool, Airtable, Notion
- Legacy systems with no modern API: Access databases, FoxPro, FileMaker, classic ASP, custom VB
- SOAP and EDI integrations for older industrial and logistics platforms
- On-premise databases: SQL Server, MySQL, Postgres, Oracle
- Vendor portals with login flows, sometimes via screen automation when no API exists
- Multi-tenant SaaS with role-scoped tokens and API key management
How We Work With You
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Step 1 — Discovery
We sit with the people who actually use the application. We learn the workflows, the gotchas, the business rules nobody documented, and the data your team really needs out of it. We also talk to whoever owns the application about what is and is not safe to touch.
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Step 2 — Design
We map the data model, propose the action allowlist, define approval gates, identify the rollback paths, and choose the right integration approach: direct API, database, message queue, or controlled automation. You see the design and the limits before we write a line of code.
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Step 3 — Build
We develop the connector inside your environment, test it against a sandbox or staging instance of the application, document the behavior, and pilot with a small group before broader rollout.
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Step 4 — Manage
We monitor, patch, and improve the connector as the application changes. When the vendor updates the API, when a workflow gets added, when the business rules shift, we adjust. You do not inherit a brittle script you have to maintain yourself.
When the App Has No API.
Some of the most valuable line-of-business applications have no modern API at all. A vendor portal that requires a browser session. A desktop tool that exports CSV and nothing else. A database the original developer locked down decades ago. We have a measured approach to these. Sometimes the right answer is a controlled screen-automation layer behind the MCP server. Sometimes it is a daily export pipeline that the AI queries from. Sometimes it is a conversation with the vendor about adding API access. We will tell you which path is right for your situation, and we will not pretend the app supports something it does not.
Built for Teams of 5 to 500 With a Critical Custom App.
This is built for organizations with at least one application that does not fit the standard catalog:
- A business running on an internal tool that no off-the-shelf AI assistant knows about.
- A practice with a vertical platform critical to operations and invisible to general-purpose AI.
- An operations team using a legacy system everyone wants to retire but cannot, yet.
- A company with three or four small custom applications that together hold the real workflow.
- A leadership team that has been told by general AI vendors that their stack is "not supported."
Tell Us About the App
That Runs Your Business.
Even a quick walkthrough is enough for us to see whether a controlled connector is feasible, what it would expose, and what it would cost to build and run.
- No sales script. A real conversation with someone who has been inside businesses like yours.
- A 30 minute call, an honest read on where AI fits and where it does not.
- Straight pricing. No surprise invoices.
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