About MCP

Al Integration with MCP Model Context Protocol

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Before VS After MCP

Model Context Protocol

  • The Model Context Protocol (MCP) workflow shows how MCP Clients in AI hosts like Claude and ChatGPT send requests to the MCP Server.
  • The MCP Server retrieves data from diverse sources, including files, databases, and APIs.
  • The workflow emphasizes standardized communication between AI clients and the server.
  • Key features include tool discovery for identifying available functions and capabilities.
  • Resource management ensures organized and efficient access to data.
  • Secure data handling is incorporated to maintain safe and trusted interactions.
  • This workflow enables seamless and efficient AI integration across multiple data environments.

Securing Lifecycle of MCP

Model Context Protocol

The Model Context Protocol (MCP) ecosystem showcases how MCP Clients integrated into AI hosts like Claude and ChatGPT interact with the MCP Server to access a wide range of data sources, including files, databases, and APIs. It emphasizes the protocol’s standardized framework, which supports tool discovery, resource management, and secure data exchange, enhancing AI functionality.

How to Choose an AI Model

Model Context Protocol

The Model Context Protocol (MCP) architecture illustrates how MCP Clients within AI hosts like Claude and ChatGPT communicate with the MCP Server to access a variety of data sources, including files, databases, and APIs. It highlights the protocol’s standardized approach, which incorporates tool discovery, resource management, and secure data exchange to enhance AI efficiency.

Feature Requirement

Data Type & Size

Easy Integration

Model Complexity

Model Performance

Data Processing Speed

Problem Your Business Faces

Model Explainability

Training Time & Expenses

MCP, Model Context Protocol

  • The Model Context Protocol (MCP) ecosystem shows how MCP Clients in AI hosts like Claude and ChatGPT connect to the MCP Server.
  • MCP Clients can seamlessly access diverse data sources, including files, databases, and APIs.
  • The ecosystem emphasizes standardized communication methods within MCP.
  • Tool discovery allows AI hosts to identify available functions and capabilities.
  • Resource management ensures efficient and organized access to data.
  • Secure data transactions maintain safe and trusted interactions.
  • This architecture optimizes AI performance and integration across various data environments.

Before VS After MCP

  • The Model Context Protocol (MCP) architecture illustrates how MCP Clients embedded in AI hosts like Claude and ChatGPT interact with the MCP Server.
  • MCP Clients access diverse data sources, including files, databases, and APIs.
  • The architecture emphasizes a standardized communication framework for consistent interactions.
  • Tool discovery enables AI hosts to identify and utilize available functions.
  • Resource management ensures organized and efficient data access.
  • Secure data handling maintains safe and trusted transactions.
  • This architecture helps boost AI performance across various data environments.

MCP Architecture

  • The overview highlights the Model Context Protocol (MCP) architecture.
  • MCP Clients within AI hosts like Claude and ChatGPT connect to the MCP Server.
  • Clients can access a variety of data sources, including files, databases, and APIs.
  • The architecture emphasizes a standardized communication system.
  • Tool discovery enables identification and use of available functions.
  • Resource management ensures efficient and organized data access.
  • Secure data exchange maintains safe and trusted interactions.
  • These features collectively enhance AI efficiency across different environments.

Impact of MCP

  • The overview presents the Model Context Protocol (MCP) architecture.
  • MCP Clients within AI hosts like Claude and ChatGPT connect to the MCP Server.
  • Clients access various data sources, including files, databases, and APIs.
  • The architecture emphasizes a standardized communication framework.
  • Tool discovery allows AI hosts to identify and utilize available functions.
  • Resource management ensures organized and efficient access to data.
  • Secure data exchange maintains safe and trusted interactions.
  • These features collectively enhance AI performance across different data environments.

Communication Protocols for AI Agents

The overview presents the Model Context Protocol (MCP) architecture, illustrating how MCP Clients within AI hosts like Claude and ChatGPT link to the MCP Server to access various data sources, including files, databases, and APIs. It underscores the protocol’s standardized communication framework, featuring tool discovery, resource management, and secure data exchange to improve AI performance. 

MCP Client Connection

Model Context Protocol

  • The overview showcases the Model Context Protocol (MCP) architecture.
  • MCP Clients within AI hosts like Claude and ChatGPT connect to the MCP Server.
  • Clients access diverse data sources, including files, databases, and APIs.
  • The architecture highlights a standardized communication system.
  • Tool discovery enables AI hosts to identify and use available functions.
  • Resource management ensures organized and efficient data access.
  • Secure data exchange maintains safe and trusted interactions.
  • These features collectively enhance AI efficiency across different environments.

MCP-Powered Agentic rag Workflow

Model Context Protocol

  • The overview depicts the Model Context Protocol (MCP) architecture.
  • MCP Clients within AI hosts like Claude and ChatGPT connect to the MCP Server.
  • Clients retrieve data from various sources, including files, databases, and APIs.
  • The architecture emphasizes a standardized communication structure.
  • Tool discovery allows AI hosts to identify and utilize available functions.
  • Resource management ensures organized and efficient data access.
  • Secure data exchange maintains safe and trusted interactions.
  • These features collectively boost AI efficiency across diverse environments.
  • The overview illustrates the Model Context Protocol (MCP) architecture.
  • MCP Clients within AI hosts like Claude and ChatGPT interface with the MCP Server.
  • Clients access a variety of data sources, including files, databases, and APIs.
  • The architecture emphasizes a standardized communication framework.
  • Tool discovery enables AI hosts to identify and utilize available functions.
  • Resource management ensures organized and efficient data access.
  • Secure data exchange maintains safe and trusted interactions.
  • These features collectively optimize AI performance across diverse environments.

The Values That Drive What We Do

Innovation

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Hard work

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Passion

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Team Work

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Our story in numbers

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Founded 8 years ago

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Tracked Events

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Active Users

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Tracked Users

Meet Our Amazing team behind the Software

Linette Law

Linette Law

Founder Soffy

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Henry Simmons

Henry Simmons

CEO Soffy

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Sophia Baxter

Sophia Baxter

Software Engineer

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Aubrey Webster

Aubrey Webster

Front End Developer

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