📢 Announcing our research paper: Zentry achieves 26% higher accuracy than OpenAI Memory, 91% lower latency, and 90% token savings! Read the paper to learn how we're revolutionizing AI agent memory.

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Integrating Zentry as an MCP Server in Cursor

Zentry is a powerful tool designed to enhance AI-driven workflows, particularly in code generation and contextual memory. In this guide, we’ll walk through integrating Zentry as an MCP (Model Context Protocol) server within Cursor, an AI-powered coding editor.

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Prerequisites

Before proceeding, ensure you have the following installed:

  • Cursor IDE
  • Python (>=3.8)
  • Git
  • Zentry-mcp (Clone the repository and set up as per the instructions in the README)

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Configuring Cursor to use Zentry as an MCP Server

  1. Open Cursor.
  2. Navigate to Settings > Cursor Settings > Features > MCP Servers.
  3. Add a new provider using the MCP server:
    • Click on Add new MCP server
    • Provide a name for the server, e.g. Zentry and select type as sse
    • Enter the SSE Endpoint: http://0.0.0.0:8080/sse
  4. Save and Restart Cursor to apply changes.

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Demo

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Using Zentry in Cursor

Once integrated, Zentry can assist with contextual memory and AI-driven coding enhancements. Some key functionalities include:

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1. Storing Coding Preferences

Zentry can store and manage coding preferences, including:

  • Complete code snippets with dependencies
  • Language/framework versions
  • Documentation and comments
  • Best practices and example usage

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2. Retrieving Stored Preferences

Access all stored coding references to:

  • Review implementations
  • Maintain consistency in coding practices

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3. Semantic Search for Preferences

Use natural language queries to find:

  • Code snippets
  • Technical documentation
  • Best practices
  • Setup guides

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Benefits of Using Zentry in Cursor

  • Persistent Context Storage: Retain and reuse coding insights across sessions.
  • Seamless Integration: Works directly within Cursor as an MCP server.
  • Efficient Search: Retrieve relevant coding insights using semantic search.

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Conclusion

By integrating Zentry as an MCP server within Cursor, you enhance your development workflow with AI-powered memory and context-aware assistance. Follow the steps above to set up and start leveraging Zentry in your coding environment.

For more details on MCP integration, refer to Cursor’s Model Context Protocol documentation.