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enquiry:+91-9121642626MCP server development: connect your AI assistant to what it actually needs
Tvisha builds custom MCP servers that connect Claude, Claude Code, and other MCP-compatible AI assistants to your internal tools, APIs, and data - through Anthropic's open Model Context Protocol, with authentication and access control built in from the start. Part of our full range of AI development services.
What is MCP server development?
The Model Context Protocol (MCP) is an open standard, introduced by Anthropic, for connecting AI assistants to external tools and data through one consistent interface - instead of a bespoke plugin per AI product. Model Context Protocol development is building and hosting that server for your specific systems: the resources, tools, and prompts it exposes, plus the authentication and permissions an enterprise deployment needs.
Resources · Tools · Prompts - one server, many AI clients
Resources
Data the model can read - files, records, API responses - as real context.
Tools
Actions the model can call, with real inputs and outputs.
Prompts
Reusable instructions a client can trigger as a defined task.
Get a Free Consultation
Tell us what you're looking for and we'll get back to you.
Prefer to talk it through?
Our team is a call away in both India and the USA.
From protocol design to production deployment
We handle the full scope of MCP server development and the AI tool integration work around it - from protocol-level design to a server your team can actually rely on.
Custom MCP Servers
Purpose-built servers exposing your APIs, databases, and internal tools through MCP, so any compatible AI assistant can use them. Typically written in TypeScript on Node.js.
Tool & Resource Design
Well-scoped tool definitions and resource schemas, so a model calls the right function with the right arguments, every time.
Authentication & Access Control
OAuth, API keys, and scoped permissions, so an AI assistant only sees and does what a given user is allowed to.
Remote & Hosted MCP
Servers deployed as a hosted HTTP endpoint, not just a local process, so a whole team can connect without installing anything.
Multi-Client Support
Built and tested against Claude Desktop, Claude Code, and other MCP-compatible clients, not one client in isolation.
Testing & Observability
Logging, tracing, and evaluation of tool calls, so you can see what a model actually did and why.
Legacy System Integration
Wrapping existing APIs, databases, and internal tools that were never built with AI access in mind.
Where teams put MCP servers to work
Claude MCP development is where most engagements start, since Claude Desktop and Claude Code are the most common MCP clients today - but the same server works with any MCP-compatible AI assistant.
Internal Knowledge Access
An assistant that queries your wikis, tickets, and databases directly through MCP tools, not a static export.
DevOps & Infra Automation
Claude Code and CI agents triggering deploys, reading logs, and querying infrastructure through a safely scoped MCP server.
Customer Support Systems
Support agents, human or AI, pulling order status, account data, and history through the same MCP tools.
SaaS Product Copilots
A product's own AI features backed by an MCP server that exposes the product's own APIs to a model - paired with custom LLM development when the underlying model needs adapting too.
Enterprise Data Governance
One server enforcing consistent access rules across every AI client that connects, instead of per-tool exceptions.
Multi-Agent Workflows
Several agents and tools sharing one MCP server as a common interface to the same underlying systems - see our agentic AI development service.
From discovery to a server your team relies on
MCP server development runs in small, verifiable stages - each one checked against your real systems before the next begins.
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01
Discovery & Tool Mapping
Which systems, APIs, and data sources the assistant should reach, and under what permissions.
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02
Server Design
Resources, tools, and prompts scoped and named so a model calls them correctly.
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03
Build & Integrate
The MCP server built against your real systems, not a mock.
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04
Secure & Deploy
Auth and scoping in place, then a local or hosted-remote rollout.
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05
Monitor & Extend
Logging and tracing from day one, then new tools added as needs grow.
The MCP stack we build on
Our MCP integration services span the protocol, its transports, and every major MCP client we've come across.
Is this a fit for you?
MCP server development pays off fastest once you're past a single script or plugin. If most of these describe you, it's worth a conversation.
More than one AI client to support
Claude Desktop today, Claude Code tomorrow, another MCP client next quarter.
Internal tools worth exposing
APIs, databases, or internal systems an AI assistant could genuinely act on.
Access rules that actually matter
Different users or teams should see and do different things through the assistant.
Growing past ad hoc scripts
One-off Slack bots and hard-coded plugins have started multiplying and duplicating logic.
Point-to-point integrations vs. one MCP server
A single custom integration is the right call for a single tool. It stops being enough once more than one AI client, or more than one system, is involved.
- A separate custom integration for every AI tool you want to support
- Access rules re-implemented and re-audited every time
- Breaks the moment a new AI client shows up
- Built once, used by every MCP-compatible client
- Authentication and permissions enforced in a single place
- New AI clients connect without new integration work
Why enterprises trust Tvisha with their MCP work
The same reasons that make this a fit for you also make us the team to build it with.
MCP-native from day one
We design tools and resources against the current MCP specification, so they work the way Claude and other MCP clients expect.
Security built around real permissions
Every server we ship maps to your existing auth and access rules, not a generic API key.
Enterprise delivery discipline
20+ years and 500+ projects of software delivery experience sit behind every MCP server we build.
A dedicated in-house team
100+ developers across two offices work your engagement directly, from protocol design through production.
An MCP server development company you can verify
Numbers you can check, not just claim.
Questions we get asked
The ones that come up on nearly every first call about MCP server development.
What is an MCP server?
An MCP server is a program that exposes your tools, data and systems to AI assistants through the Model Context Protocol - Anthropic's open standard for connecting AI models to external systems. It defines resources the model can read, tools the model can call, and prompts, so any MCP-compatible client can use them the same way.
Which AI assistants can connect to an MCP server?
Any MCP-compatible client - Claude Desktop, Claude Code, and the growing set of MCP-compatible applications and IDEs. MCP is an open standard, not tied to a single vendor's product.
Do you build the server as a local process or a hosted service?
Both, depending on your needs. A local server over stdio is simplest for a single developer's machine; a hosted remote server over HTTP lets a whole team or a production application connect without installing anything.
How do you handle authentication and permissions?
Through OAuth or scoped API keys mapped to your existing access rules, so the assistant only sees and does what a given user is already allowed to. This is a defined stage in every engagement, not an afterthought.
Can you connect an MCP server to our existing APIs and databases?
Yes. Most MCP server development work is wrapping systems that already exist - REST APIs, databases, internal tools - so an AI assistant can use them through one consistent interface.
More AI and agent development services
Ready to give your AI assistant real access to your systems?
Tell us which tools and data you want connected and we'll scope the MCP server.
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