MCP development
A Model Context Protocol server lets Claude, Cursor and other AI assistants read your data and use your tools through one defined interface. We design it, build it and hand it to your team.
Claude, Cursor or your own agent asks for something.
Offers a short list of tools and checks every call.
A database, an API or an internal tool. The credentials stay here.
The assistant never holds your database password.
01 / Built and operated by NSDBytes
Our own AI product. India market news as short briefings on Telegram and Web Chat, each story linked to the listed company, commodity, index or currency it concerns. Add the address below to your assistant and try it before you speak to us.
https://
Add this address to Claude, Cursor or any MCP client.
search_stories · One read-only toolListed in
A client project. FocusPulse is our own product, and we have no published case study of an MCP server built for a client.
02 / Is this the one
MCP is one way to connect AI to software, not the only one. It earns its place when more than one assistant needs the same access.
03 / What the work covers
Most servers start small: a few read-only tools, tested in the assistants you use, then widened.
Which data and actions the server offers, each described so a model picks the right one.
Input checks, sign-in, permissions for each client, rate limits and a log of every call.
Tested in the assistants your team uses, including requests the server should refuse.
Code, deployment and documentation go to your team. A public server can be listed in the directories.
04 / Limits and risks
If a tool can delete records, a confused model can ask it to. We start read-only and add write actions one at a time.
Text a model reads can carry instructions. The server enforces its own rules and treats every call as untrusted.
MCP changes often and assistants differ in what they support. Plan for some maintenance.
05 / What to do next
The first step is a free scoping call about one system and the assistants your team uses. A written estimate follows.
A little clarity
The Model Context Protocol is an open standard for connecting AI assistants to data and tools. An MCP server exposes a defined set of your data and actions once, and any assistant that supports the protocol can use it. It is worth building when AI should work with your own systems through one controlled interface.
Yes, for our own product. FocusPulse runs a public MCP server. Free beta. No account or key. It is listed in the Claude Connectors Directory, Official MCP Registry, Smithery and Glama. We have no published case study of an MCP server built for a client, so FocusPulse is the example to judge us by.
Resources are data an assistant can read, such as a record or a document. Tools are actions it can ask the server to carry out, such as a search or an update. Prompts are ready-made instructions the server offers for common tasks. Most servers start with a few read-only tools.
The server does not depend on a model. Any client that supports the protocol can connect, whichever model sits behind it. What differs is the client: each assistant supports a slightly different set of MCP features, so we test in the ones you plan to use.
It depends on how many tools the server offers and how ready your systems are to be connected. First releases at NSDBytes start from $5,000. The project cost estimator gives a range for an AI build, and a fixed quote follows a free scoping call. Hosting and AI model usage are billed by their providers and are separate.
Start wherever you are
We’ll help you decide which tools to offer, what must stay off limits and what a first server involves.