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MCP (Model Context Protocol) is an open-source standardized protocol developed by Anthropic to connect large language models (like Claude) with external data sources, tools, and prompt systems. Its core mission is to break down information silos between AI and data through unified interfaces for secure, efficient integration.

Eliminates fragmented integration: Traditional AI systems require custom interfaces for each data source, while MCP provides a universal protocol to reduce redundant development. Enhanced security: Servers maintain full control over resources, avoiding exposure of sensitive information like API keys. Improved scalability: Supports dynamic connection of new data sources or tools without modifying core model code.

MCP Server: Hosts actual data, tools, and prompts (e.g., enterprise document databases or API gateways). MCP Client: Integrated into AI applications (like Claude Desktop) to establish secure connections. Protocol Specifications: Defines communication formats, authentication methods, and access control rules (like OAuth 2.0).

1. Exposes resources: Servers provide data (files, databases) or tools (APIs) through standardized interfaces. 2. Secure connection: Establishes encrypted one-to-one channels with clients to ensure data confidentiality. 3. Dynamic response: Returns real-time information (database query results) or executes operations (API calls) based on AI requests.

AI-powered development environments: Connect code repositories and documentation for context-aware programming assistance. Enterprise knowledge assistants: Integrate internal wikis and CRM data for precise Q&A. Automated workflows: Execute bookings, approvals, and other operations through API tools.

Current capability: Supports connection to local MCP servers (e.g., personal document libraries). Future plans: Will expand to enterprise remote servers for cross-team collaboration.

Resource isolation: Servers fully control data access permissions—AI models cannot bypass restrictions. Zero key sharing: No need to share API keys with LLM providers like Anthropic. Audit logs: All access activities are traceable for compliance requirements.

Development Cost: Traditional methods require custom development per data source. MCP Connect once, reuse everywhere. Maintenance: Traditional version upgrades need individual adaptation. MCP protocol ensures smooth transitions. Security: Traditional methods have scattered key management. MCP provides centralized control.

Open protocol: Community contributions encouraged (e.g., MySQL/Slack connectors). Enterprise support: Anthropic plans managed MCP server services.

MCP: Focuses on protocol standardization, led by Anthropic with deep Claude integration. LangChain: Emphasizes multi-model chaining with high flexibility but requires manual compatibility handling.