What is MCP Server and how it works?
As AI assistants gain sophistication, access to the proper, real-time data remains a huge challenge. AI models only as strong as the data on which they run, but most AI tools now are stuck in data silos, needing customized integrations per new system.
To solve this, we’re introducing Model Context Protocol (MCP)—an open-source standard designed to seamlessly connect AI assistants with business tools, content repositories, and development environments. By standardizing AI-to-data interactions, MCP allows AI models to deliver more accurate, contextual, and insightful responses while reducing integration complexity for developers.
MCP acts like a universal USB-C for AI—plug, connect, and go.
What Is Model Context Protocol (MCP)?
MCP is a universal, open standard that enables secure, two-way connections between AI systems and data repositories. By replacing custom integrations with a single protocol, MCP empowers developers to seamlessly link AI tools to content platforms, business software, and development environments.
Core Components of MCP:
- MCP Specification & SDKs: A standardized framework for building connectors.
- Local MCP Server Support: Integrated into Claude Desktop apps for real-time testing.
- Open-Source Repository: Pre-built MCP servers for Google Drive, Slack, GitHub, and more.
Why MCP server?
Break Down Data Silos
MCP removes the requirement for isolated, single-instance integrations. Developers can integrate AI tools with various data sources—from Postgres databases to Puppeteer scripts—via one protocol.
Accelerate Development
With Claude 3.5 Sonnet’s capability to quickly create MCP servers, organizations can roll out context-aware AI in days, not months. Pre-configured connectors for Slack, GitHub, and other platforms lower setup time even further.
Improve AI Accuracy
By providing AI models with real-time access to context-relevant data, MCP provides responses grounded in current context. Early adopters such as Block experience fewer iterations and more functional results in coding operations.
Enterprise-Ready Security
MCP also facilitates secure connections for internal infrastructures, making it suitable for customers of Claude for Work who handle sensitive datasets.
How MCP server Works?
MCP makes it possible to have secure two-way communication between AI tools and data sources. Developers can:
Host an MCP server to open their datasets in a secure manner.
Develop an MCP client so that AI tools can fetch and engage with structured data.
As part of streamlining adoption, we are making available the significant parts of the Model Context
Protocol under open source:
- MCP Specification and SDKs – Allowing developers to construct custom MCP implementations.
- On-Premises MCP Server Support – Built into Claude Desktop apps to enable frictionless AI-data integration.
- Pre-Built MCP Servers – Ready-to-use integrators for Google Drive, Slack, GitHub, Git, Postgres, and Puppeteer.
Getting Started with MCP
- Install Pre-Built Connectors: Use the Claude Desktop app to deploy MCP servers for Google Drive, Git, or Slack.
- Build Custom Servers: Follow the quickstart guide and SDKs to create tailored integrations.
- Join the Open-Source Community: Contribute to repositories or adapt existing implementations for your needs.
For Enterprises:
Claude for Work users can test MCP servers locally today, with remote production deployment toolkits coming soon.
Real-World MCP Use Case: How I Use It Daily
MCP Marketplace (Cline, WindSurf, Cursor)
If you’re using AI-enhanced tools like Cline, WindSurf, or Cursor, you might’ve seen a new feature called MCP Marketplace—a one-click way to add AI capabilities.
Instead of following a 20-step tutorial to get an AI tool working, I now just paste a link into an MCP config file, and boom—it’s active.
Example: If I want AI-powered code reviews inside my dev environment, I just install the relevant MCP server. No custom scripts needed.
Sequential Thinker (For Better AI Reasoning in Coding)
If you’ve ever had an AI assistant say,
“Let me think… actually, wait, let me re-check”
…then Sequential Thinker is your new best friend.
This MCP breaks down complex problems into structured steps—so when we are coding, it helps ensure the AI doesn’t jump to incorrect conclusions.
🔧 Setup Example (Node.js via NPX):
json{
"mcpServers": {
"sequential-thinking": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-sequential-thinking"
]
}
}
}The Future of MCP: Working Together and Expansion
MCP is not just a protocol—it’s a grass-roots movement. Through open-source collaboration, the ecosystem hopes to:
- Increase connector libraries for specialized tools.
- Allow AI systems to keep context throughout workflows.
- Make enterprise-grade AI integration more accessible to the masses.
Join the MCP Community
MCP is not just a protocol—it’s an open, collaborative movement toward AI-driven workflows. If you’re an enterprise user, an AI developer, or an early adopter, we encourage you to join the movement and contribute to the future of context-aware AI.
Build today! Let’s close the gap between AI and real-world data.
