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    AI Architecture
    architecture

    What Is the Model Context Protocol (MCP)?

    AsterMind Team

    The Model Context Protocol (MCP) is an open standard created by Anthropic for building secure, two-way connections between AI assistants and external data sources, tools, and services. MCP replaces fragmented, custom integrations with a universal protocol — like a "USB-C for AI" — allowing any MCP-compatible AI system to connect to any MCP-compatible data source.

    Why MCP Was Created

    Before MCP, connecting AI to external tools required custom implementations for each combination of AI model and data source. This created:

    • Integration sprawl — N models × M tools = N×M custom connectors
    • Fragmented ecosystems — Each AI provider had its own integration approach
    • Security risks — Inconsistent authentication and authorization
    • Maintenance burden — Custom connectors required ongoing upkeep

    MCP solves this with a single, standardized protocol that any AI system can implement.

    How MCP Works

    Architecture

    MCP uses a client-server architecture:

    • MCP Hosts — AI applications that need to access external data (Claude Desktop, IDEs, AI agents)
    • MCP Clients — Protocol clients within the host that manage connections to servers
    • MCP Servers — Lightweight services that expose specific data sources or tools through the standardized protocol

    Key Capabilities

    Capability Description
    Resources Expose data from files, databases, or APIs for the AI to read
    Tools Define actions the AI can invoke (search, create, update, delete)
    Prompts Provide reusable prompt templates with context
    Sampling Allow servers to request LLM completions through the client

    Protocol Flow

    1. AI host connects to one or more MCP servers
    2. Servers declare their available resources and tools
    3. When the AI needs external data, it sends a request via MCP
    4. The server processes the request and returns results
    5. The AI incorporates the data into its response or workflow

    Adoption

    MCP has been adopted across the AI industry:

    • Anthropic — Claude Desktop and Claude Agent SDK
    • OpenAI — Integrated MCP support
    • Google — MCP compatibility in Gemini ecosystem
    • Microsoft — MCP support in development tools
    • Community — Thousands of open-source MCP servers for tools like GitHub, Slack, Google Drive, PostgreSQL, and more

    MCP vs. Function Calling

    Feature Function Calling MCP
    Standard Provider-specific Universal open standard
    Discovery Manual schema definition Automatic capability discovery
    Security Varies by implementation Built-in auth and permissions
    Ecosystem Tied to one provider Cross-provider compatibility
    Composability Limited Multiple servers can be combined

    Building with MCP

    MCP Servers

    Expose your data or tools through the MCP protocol. SDKs are available for TypeScript, Python, and other languages.

    MCP Clients

    Build AI applications that can connect to any MCP server, automatically discovering and using available tools and resources.

    Further Reading