MCP Servers for TensorFlow

TensorFlow is an open-source machine learning framework developed by Google that provides a comprehensive ecosystem of tools for building and deploying machine learning models.

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  • Why this server?

    Mentioned as an example repository that can be analyzed using the remote codebase feature to understand specific components like testing frameworks

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    A Model Context Protocol server that enables AI agents to retrieve and understand entire codebases at once, providing tools to analyze local workspaces or remote GitHub repositories.
    3
    TypeScript
    MIT License
    • Linux
    • Apple
  • Why this server?

    Uses TensorFlow.js for efficient tensor operations in implementing the neural memory model

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    A neural memory system that learns and predicts sequences, maintaining state via memory vectors for enhanced code generation and understanding.
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    44
    TypeScript
  • Why this server?

    Uses TensorFlow.js for efficient tensor operations in the neural memory model with operations wrapped in tf.tidy() for proper memory management

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    Enables neural memory sequence learning with a memory-augmented model for improved code understanding and generation, featuring state management, novelty detection, and model persistence.
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    44
    TypeScript
  • Why this server?

    Detects TensorFlow installations and reports on GPU availability for AI development.

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    An MCP server that provides detailed information about your development environment to the Cursor code editor, enabling more context-aware assistance.
    1
    Python
    • Linux
    • Apple