An MCP Server is a component that implements the Model Context Protocol (MCP), an open standard introduced by Anthropic in November 2024 that enables secure, standardized connections between AI systems (like large language models) and external data sources, tools, and services.
MCP servers act as bridges that expose your data and capabilities to AI applications in a consistent, interoperable way. Instead of building custom integrations for every AI tool, you can create one MCP server that works with any MCP-compatible client.
Understanding the Model Context Protocol (MCP)
The Model Context Protocol is an open standard and open-source framework designed to standardize how artificial intelligence systems integrate and share data with external tools, systems, and data sources.
Before MCP, each AI application required its own custom integration for every data source or tool. MCP solves this fragmentation by providing a universal protocol that both data providers (MCP servers) and AI applications (MCP clients) can implement.
How MCP Servers Work
Architecture
The MCP architecture consists of three main components:
- MCP Servers - Expose data sources, tools, and capabilities through a standardized interface
- MCP Clients - AI applications (like Claude, ChatGPT) that connect to MCP servers to access data and tools
- MCP Protocol - The standardized communication protocol that defines how clients and servers interact
Server Responsibilities
An MCP server can provide three types of capabilities:
Resources - Expose data sources like databases, file systems, or APIs that the AI can read
Tools - Provide executable functions the AI can invoke (e.g., sending emails, creating calendar events, running queries)
Prompts - Offer pre-defined prompt templates that guide AI interactions
Communication Flow
- An MCP client (AI application) discovers available MCP servers
- The client connects to a server using the MCP protocol
- The server exposes its resources, tools, and prompts
- The AI can then access data or invoke tools through standardized requests
- The server processes requests and returns responses
Major Developments in 2025
November 2025 - One Year Anniversary
On the one-year anniversary of MCP's release, the 2025-11-25 specification was published with highly-anticipated features requested by the community for production deployments.
December 2025 - Foundation Donation
Anthropic donated the Model Context Protocol to the Agentic AI Foundation (AAIF), a directed fund under the Linux Foundation. The foundation was co-founded by Anthropic, Block, and OpenAI with support from other companies, ensuring MCP's future as a community-driven standard.
March 2025 - OpenAI Adoption
OpenAI officially adopted MCP in March 2025, integrating the standard across its products including the ChatGPT desktop app. This marked a significant milestone in MCP becoming the industry standard for AI tool connections.
Rapid Adoption and Ecosystem Growth
Since launching in November 2024, MCP has seen extraordinary adoption:
- Thousands of MCP servers built by the community
- Official SDKs available for all major programming languages
- 97M+ monthly SDK downloads across Python and TypeScript
- Industry-wide adoption as the de facto standard for connecting agents to tools and data
Creating an MCP Server
Available SDKs
Official Software Development Kits are available for:
- Python - For Python-based server implementations
- TypeScript/JavaScript - For Node.js server implementations
- Community SDKs - Additional languages supported by the community
Basic Server Structure
An MCP server typically:
- Defines what resources, tools, and prompts it exposes
- Implements handlers for client requests
- Manages authentication and security
- Handles errors and edge cases
Example Use Cases
Database Server - Expose database query capabilities to AI systems
File System Server - Allow AI to read and search file contents
API Integration Server - Connect AI to external services (Slack, GitHub, Google Calendar)
Custom Tool Server - Provide domain-specific functionality
MCP Clients
While MCP servers provide capabilities, MCP clients consume them. Notable MCP clients include:
- Claude Desktop App (Anthropic)
- ChatGPT Desktop App (OpenAI)
- Custom AI Applications - Any developer can build MCP client support
Benefits of MCP Servers
For Data Providers
Build Once, Use Everywhere - One MCP server works with all MCP-compatible AI clients
Standardized Interface - No need to learn different integration methods for each AI platform
Open Standard - Not locked into proprietary protocols
Community Support - Large ecosystem with shared tools and examples
For AI Application Developers
Easy Integration - Connect to thousands of existing MCP servers
Consistent Experience - All servers use the same protocol
Reduced Development Time - No custom integrations for each data source
Future-Proof - New servers automatically work with existing clients
For Users
Better AI Capabilities - AI systems can access relevant data and tools
Flexibility - Choose which data sources to connect
Privacy Control - Direct connections without third-party intermediaries
Extensibility - Add new capabilities without waiting for platform updates
Security Considerations
In April 2025, security researchers identified several security challenges with MCP:
Known Security Issues
Prompt Injection - Malicious inputs could manipulate AI behavior through MCP servers
Tool Permissions - Combining tools can create unintended data exfiltration paths
Lookalike Tools - Malicious servers could silently replace trusted tools
Best Practices
- Implement proper authentication and authorization
- Validate all inputs and outputs
- Use principle of least privilege
- Monitor server access and usage
- Keep SDKs and dependencies updated
- Review security guidelines from the MCP community
The Future of MCP
As an open standard managed by the Agentic AI Foundation, MCP's future development will be community-driven. Expected areas of growth include:
- Enhanced security features and guidelines
- Expanded protocol capabilities
- Better tooling for server development and testing
- Standardized authentication mechanisms
- Performance optimizations
Frequently Asked Questions (FAQ)
What does MCP stand for?
MCP stands for Model Context Protocol, an open standard for connecting AI systems to data sources and tools.
Who created the Model Context Protocol?
Anthropic introduced MCP in November 2024. In December 2025, it was donated to the Agentic AI Foundation (a Linux Foundation project) co-founded by Anthropic, Block, and OpenAI.
What is the difference between an MCP server and an MCP client?
An MCP server exposes data and tools to AI systems. An MCP client is an AI application that connects to MCP servers to access those capabilities. Servers provide; clients consume.
Do I need to be a developer to use MCP?
To create an MCP server, yes, you need programming knowledge. However, to use existing MCP servers with MCP-compatible AI applications like Claude or ChatGPT, you typically just need to install and configure them.
What programming languages can I use to build MCP servers?
Official SDKs exist for Python and TypeScript/JavaScript, with community-contributed SDKs for other major programming languages.
Is MCP open source?
Yes, MCP is both an open standard (anyone can implement it) and open source (the reference implementations and SDKs are publicly available on GitHub).
Which AI systems support MCP?
As of 2025, major AI systems supporting MCP include Anthropic's Claude (desktop app) and OpenAI's ChatGPT (desktop app). The list continues to grow as MCP becomes the industry standard.
Can I use MCP in production?
Yes, MCP is designed for production use. The 2025-11-25 specification included features specifically requested by organizations deploying MCP in production scenarios.
Are there security risks with MCP servers?
Like any system that connects external data to applications, MCP servers require proper security implementation. Known considerations include prompt injection risks, tool permission management, and server authentication. Following security best practices is essential.
How many MCP servers are available?
The community has built thousands of MCP servers since November 2024, covering databases, file systems, APIs, cloud services, and custom tools. The ecosystem continues to grow rapidly.
Can I monetize an MCP server?
Yes, there's no restriction on commercial MCP servers. You can create paid MCP servers that provide premium data or tools to AI applications.
