Your customers have started asking the AI assistants they already use, such as Claude, ChatGPT and Cursor, to do work in the tools they pay for. The Model Context Protocol (MCP) is the open standard that makes that possible: an MCP server describes what your product can do as a set of tools, and any assistant that supports MCP can call them on the user's behalf. I'm Md. Emamul Mursalin, a freelance AI developer, and I build MCP servers for SaaS products at a fixed price for teams in the US, UK, Saudi Arabia and the Gulf.
The protocol is the easy part. The hard part is deciding which actions an assistant should be allowed to take, making sure each user can only reach their own data, and keeping a record of what was done. Those are the parts I design first, because they decide whether your security review says yes.
Md. Emamul Mursalin · Rajshahi, Bangladesh · remote worldwide · UTC+6 · Updated
An MCP server sits beside your existing API. It exposes a short list of tools, each with a name, a description the model reads and a strict input schema, such as search_projects, get_invoice or create_task. When a user connects your product inside Claude or ChatGPT and asks a question, the assistant picks the right tool, your server checks who the user is and what they may do, calls your API and returns the result. Your core app does not change.
It can run as a remote server over HTTP, which suits a SaaS product whose users connect from the web, or as a local server for developer tools that run on the user's own machine, such as an integration for Cursor or VS Code.
A small server that exposes read-only tools over your product's data, such as search, look-ups and reports, is scoped as my AI Integration Starter package: $799 and one to two weeks. That covers tool design and the descriptions the model reads, test cases, integration with your API, usage logging, and documentation with a handoff call.
A server that can also act, creating, updating or assigning records, needs more care: sign-in tied to your existing accounts, permissions checked per user and per role, a confirmation step before anything changes, and an audit log of every call. That is the AI Integration Professional package: $2,499 over three to five weeks, with two weeks of support after launch.
Hosting runs on your own account, and the model usage is paid by whoever runs the assistant, not by your server. If you would rather buy hours against an existing backlog, I bill $20 to $30 an hour.
Remote MCP servers sign users in with OAuth, the same kind of flow your customers already use to connect other apps. A user who connects Claude to your product signs in with their own account and gets exactly their own permissions, so the assistant can never see more than that person could in your app.
Telova is an AI teammate for Telegram that I build as a full-stack engineer at Ayana Dev Studio, where I work. It runs daily stand-ups, turns replies into tasks, blockers and logged hours, and alerts team leads when someone is stuck. Every action it can take, around 90 of them, is an MCP tool, each one audit-logged, with a confirmation step and role-based permissions. A member can ask "what's blocking my team?" or "reassign that to Sam", and it acts on the real data only within what that person is allowed to do.
The same rules carry over to a server for your product: a short list of well-described tools, permissions checked on every call, and a record of everything an assistant did.
I work remotely from Bangladesh at UTC+6, with no daylight saving: that covers the whole UK afternoon, the US East Coast morning and evening, and a Sunday-to-Thursday week shared with Saudi Arabia. The server lives in your repository and goes through pull requests your team reviews, the contract assigns all IP to you on final payment, and payment is by milestone in USD through Wise, Payoneer, bank transfer or a Stripe invoice.
Proof
“This project was handled in an excellent way. The seller understood the task clearly. Progress updates were helpful. The final output was accurate and polished. Everything arrived as promised. Glad to recommend this seller.”
Alexi Denise
Individual client
“He successfully completed all my tasks quickly and with excellent quality.”
Imran Mohammed
“Great work. Great communication, and a quick turnaround. I'd definitely order again.”
Agrossen
Fixed price
Fixed price, fixed scope. Starter and Enterprise tiers are on the pricing page.
RAG over your data plus automated workflows
$2,499/project
Launch offer$1,62435% off for the first 5 clients
3-5 weeks
Multi-tenant AI SaaS with RAG and agent workflows
$4,999/project
Launch offer$3,24935% off for the first 5 clients
5-8 weeks
Case studies with the same stack and patterns.
Costs, architecture and how-to guides from the blog.
Questions & answers
A small service that describes what your product can do as tools an AI assistant can call, using the Model Context Protocol, an open standard introduced by Anthropic and supported by Claude, ChatGPT, Cursor and other assistants. A user connects it once, then asks the assistant to search, report or act in your product.
With me, $799 for a read-only server over your product's data, built in one to two weeks. A server that can also create and update records, with OAuth sign-in, role-based permissions, confirmation steps and an audit log, is $2,499 over three to five weeks.
No. The MCP server sits beside your existing API and calls it, the same way your own frontend does. It lives in your repository, goes through pull requests your team reviews, and can be switched off without touching the product.
It is as safe as the tools you expose. Start read-only, add write actions one at a time with a confirmation step, run every call as the signed-in user with their own permissions, and keep an audit log so you can see exactly what an assistant did and for whom.
Any assistant that supports MCP. A remote server over HTTP suits Claude, ChatGPT and other assistants your customers use on the web; a local server suits developer tools such as Cursor and VS Code. I test the tools against the assistants your users actually use.
Yes. The server only needs your API, so your product can run on Rails, Django, Laravel or anything else. The server itself is TypeScript on Node.js, small enough for your team to read and maintain.
Next step
A 30-minute call is enough to tell you which package fits, what I would cut, and what it will cost to run. No pitch, no obligation.
Or email hello@mursalinsdesk.com
