Make your app something AI assistants can actually use.
The Model Context Protocol is how AI assistants connect to real tools and data. We build custom MCP servers for your product, and wire existing ones into your app, so Claude and Cursor can read your data, call your API, and act on your users' behalf.
MCP is simple in theory and messy in practice.
You want Claude or Cursor to work with your product, but every tutorial stops at a toy weather-API example
Your AI tool wrote an MCP server that runs locally and then falls over the moment anything real touches it
You do not know whether you need a server, a client, or both, and the spec keeps moving
Transport is confusing: stdio works on your laptop, but you need remote HTTP for actual users
You have no idea how to authenticate MCP requests without handing out god-mode access to your database
Enterprise agencies quoted you $25,000 or more for what should be a few days of focused work
Sound familiar? You're not alone. This is exactly why we built our mcp integration service.
We build MCP integrations that survive contact with real users.
Custom MCP servers for your product
We expose your data and actions as clean, well-described tools and resources, so Claude, Cursor, and other clients can use them reliably instead of guessing.
Remote transport, not just localhost
Streamable HTTP with proper session handling, so your MCP server works for your users on their machines, not just on yours during a demo.
Authentication and scoping done properly
OAuth flows and scoped tokens so each user reaches their own data and nothing else. No shared service keys handed out to every client.
Tool descriptions the model actually understands
Most MCP servers fail because the tool descriptions are vague and the model calls them wrong. We write and test them against real prompts until behavior is consistent.
Connecting existing MCP servers
Often the server you need already exists. We wire GitHub, Supabase, Stripe, Linear, Postgres and others into your app or workflow, and only build custom when nothing fits.
Rate limits, timeouts, and failure handling
What happens when a tool call hangs or the upstream API rate limits you? We handle it, so the assistant degrades gracefully instead of hallucinating success.
Free consultation. No commitment.
Why mcp integration matters for your vibe-coded project.
For two years, the way to add AI to a product was to bolt a chat box onto the corner of your app. MCP changes the direction of that relationship. Instead of pulling a model into your product, you make your product available to the assistants your users already work in.
That matters commercially, not just technically. If someone lives in Claude or Cursor all day, the tool that plugs into their assistant is the one that gets used. The one that requires opening another tab quietly stops getting opened.
The protocol itself is not the hard part. Wiring a tool call together is an afternoon of work. What takes real experience is everything after: authenticating a specific user rather than handing out a shared key, keeping sessions alive over remote transport, and writing tool descriptions precise enough that the model calls them correctly at three in the morning without a human watching.
This is exactly the last-twenty-percent problem, wearing new clothes. AI coding tools will happily generate an MCP server that runs on your laptop. Turning that into something your customers can safely connect to their own accounts is a different job.
The difference between a prototype and a product is in the details. MCP Integration is one of those critical details that separates apps that fail from apps that scale.
We've handled mcp integration for over 150 vibe-coded projects. We know exactly what you need and how to implement it correctly.
Every day without proper mcp integration...
A demo that never becomes a product
Your MCP server works beautifully when you demo it locally, then breaks the moment a second user connects. Local stdio transport does not become multi-user infrastructure on its own.
Credentials handed out too widely
The fastest way to ship an MCP server is one shared API key with full access. It also means any connected client can read every customer record you have.
An assistant that uses your tools wrongly
Vague tool descriptions cause models to call the wrong tool, pass malformed arguments, or loop. Users blame your product, not the description, and they are not entirely wrong.
Enterprise pricing for a small job
Agencies quote $25,000 to $120,000 for MCP work because they price for enterprise procurement. Most focused integrations do not need anything close to that.
You didn't start this project to let technical blockers stop you. You started it because you had a vision. Let us handle the mcp integration so you can bring that vision to life.
Imagine your app with mcp integration done right.
Your customer opens Claude, connects your MCP server once, and asks it to pull their data, run the thing they always run manually, and summarize the result. It works on the first try.
Each user reaches their own data through their own scoped credentials. You are not lying awake wondering whether one connected client can read another customer entire account.
When an upstream API times out, the assistant says so plainly instead of inventing a confident answer that costs you a support ticket.
You ship the integration in days, for a fraction of an enterprise quote, and your product becomes the one that lives inside the tools your users already have open.
It Just Works
Your mcp integration is solid. No more worrying.
This is what happens when you stop struggling and let experts handle the hard parts. Your vibe-coded project deserves to work flawlessly.
What you get with our mcp integration service.
Custom MCP servers built for your specific product
Existing MCP servers connected and configured
Remote HTTP transport, not localhost-only demos
OAuth and scoped, per-user authentication
Tool descriptions tested against real model behavior
Proper error handling, timeouts, and rate limiting
Works with Claude, Cursor, and other MCP clients
Clear docs so your users can connect it themselves
Our mcp integration process.
Tell us what you want the AI to do
Describe the actions and data you want exposed. We work out whether you need a custom server, an existing one, or a client integration in your own app.
We design the tool surface
We map your capabilities to MCP tools and resources, decide the auth and permission model, and share the plan before writing production code.
Build, then test against real prompts
We implement the server and exercise it with real assistant conversations, because a tool that looks correct in isolation can still be unusable in practice.
Deploy and document
Deployed with monitoring, plus setup instructions your users can follow to connect it in Claude Desktop, Cursor, or your own client.
Frequently asked questions.
What is MCP, in plain terms?
The Model Context Protocol is an open standard from Anthropic that gives AI assistants a consistent way to connect to outside tools and data. Instead of every app inventing its own integration, an assistant that speaks MCP can talk to any MCP server. In practice it means Claude or Cursor can read your data and take actions in your product through a defined, permissioned interface.
Do I actually need a custom MCP server?
Often not, and we will tell you when that is the case. There are thousands of public MCP servers already, covering GitHub, Postgres, Stripe, Linear, Supabase and many more. If one of those covers your need, connecting it is far cheaper than building. Custom work makes sense when you are exposing your own product data or your own proprietary actions.
How long does an MCP integration take?
Connecting existing MCP servers into a workflow is usually 1 to 2 days. A custom server exposing a handful of tools with proper authentication is typically 3 to 5 days. Larger surfaces with complex permission models take longer, and we give you a real timeline after reviewing what you need rather than a number chosen to win the job.
Can you make my existing app work as an MCP server?
Yes, and this is the most common request we get. If you already have an API, we can usually put an MCP layer on top of it rather than rebuilding anything. Your existing endpoints stay exactly as they are; the MCP server becomes a translation layer with its own auth and its own carefully written tool descriptions.
How do you handle authentication so users only see their own data?
We use OAuth with scoped, per-user tokens rather than a single shared key. Each connected client authenticates as a specific user and can only reach that user data. This is the part most quickly-built MCP servers get wrong, and it is the part that turns into a breach notification later.
Will this work with Cursor and other tools, or only Claude?
Any MCP-compatible client. That includes Claude Desktop, Claude Code, Cursor, and a growing list of others. Because MCP is an open standard, building the server once means it works everywhere the protocol is supported, which is the main advantage over writing a bespoke plugin per tool.
Is MCP secure enough for production use?
The protocol supports doing this properly. Whether a given server is secure depends entirely on how it was built. The common failures are shared credentials instead of per-user tokens, missing scope checks, and tools that expose more than intended. We build with those specific failure modes in mind and can audit an MCP server you already have.
Trusted by 150+ vibe coders.
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Projects Completed
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Satisfaction Rate
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Ready to get mcp integration done right?
Stop struggling with mcp integration on your own. Let our experts handle it while you focus on what matters—building your product and serving your users.
Free consultation. No commitment required.