MCP is supported by Anthropic Claude, Cursor, Windsurf, Cline, and many other AI development tools. The protocol is being adopted across the AI ecosystem as a standard for AI tool use.

MCP · MODEL CONTEXT PROTOCOL

MCP Development India — Connect AI to Everything

We build custom MCP (Model Context Protocol) servers and clients that connect your AI agents to databases, APIs, file systems, and enterprise tools using Anthropic's open standard.

Build Your MCP Server AI Agent Development

What is MCP?

Model Context Protocol — The USB-C for AI

MCP is an open standard by Anthropic that defines how AI models talk to tools, APIs, and data sources. One protocol, every connection — instead of custom integration code for every tool.

# MCP Server: Your AI agent now has access to your database
@mcp.tool()
async def query_customer_database(customer_id: str) -> dict:
    """Query customer data from your CRM via MCP"""
    result = await db.query(f"SELECT * FROM customers WHERE id='{customer_id}'")
    return result

MCP Solutions

What We Build with MCP

🗄️

Database MCP Servers

Connect your AI agents directly to PostgreSQL, MySQL, MongoDB, or Supabase — agents can query, insert, and update records using natural language.

🔌

API MCP Connectors

Expose any REST or GraphQL API as an MCP tool — your AI agents can call Stripe, Salesforce, HubSpot, or any internal API without custom code.

📁

File System MCP

Let AI agents read, write, and manage files in your cloud storage — AWS S3, Google Drive, SharePoint, or local file systems via secure MCP.

🏢

Enterprise Tool Integration

Connect AI agents to Jira, Confluence, Slack, Notion, Google Workspace, or any enterprise tool your team uses — all via MCP protocol.

🔗

Multi-Source MCP Hubs

Build MCP hubs that route agent requests to the right data source — CRM for customer data, ERP for orders, analytics for reporting — all seamlessly.

🛡️

Secure MCP Infrastructure

Production-ready MCP servers with authentication, rate limiting, audit logging, and role-based access control for enterprise deployments.

FAQ

MCP Development Questions

What is Model Context Protocol (MCP)? +

Model Context Protocol (MCP) is an open standard by Anthropic that defines how AI models connect to external tools, data sources, and systems. It provides a universal interface so AI agents can call APIs, query databases, and use tools without custom integration code for each connection.

Which AI models support MCP? +

MCP is natively supported by Anthropic Claude, and is also compatible with Cursor, Windsurf, Cline, and many AI development tools. OpenAI-based agents can also use MCP via adapter layers. The protocol is being rapidly adopted across the AI ecosystem.

Do I need MCP if I already use LangChain? +

MCP and LangChain are complementary. LangChain is a framework for building LLM applications; MCP is a protocol for AI-to-tool communication. You can use MCP within LangChain-based agents to give them standardized access to any external system.

How long does it take to build a custom MCP server? +

A simple MCP server exposing a single API or database takes 1-2 weeks. Complex multi-tool MCP hubs with authentication, logging, and enterprise features take 3-6 weeks.