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"A tool or algorithm to convert code into a tree structure" matching MCP servers:

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    Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
    Last updated
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    27
    Apache 2.0
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    Code-mode MCP server (docs_search + execute_code two-tool surface) backed by a unified capability manifest across three sandbox kernels (in-process node:vm, WASM via QuickJS / Pyodide / Wasmtime, and remote microVM via E2B / Cloudflare Sandbox). At N=30 tools the bootstrap-context cost drops to 13.6% of direct tool-use. Apache-2.0.
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    Apache 2.0
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    Analyzes source code structure across multiple languages using tree-sitter, extracting classes, functions, methods, and metadata with precise line numbers for efficient codebase exploration and AI-assisted development.
    Last updated
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    MIT
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    Enables AI applications to write and execute natural language queries on organizational data stored in DX Data Cloud's Postgres database. Runs locally and provides a query tool for AI assistants to formulate and execute database queries with user approval.
    Last updated
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    9
    MIT
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    An MCP server framework featuring dynamic tool loading and a modular one-tool-per-file architecture for rapid development. It supports both Stdio and HTTP transport modes, offering automated test generation and centralized configuration management.
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    A Model Context Protocol server framework featuring dynamic tool loading and automatic tool discovery from a dedicated directory. It leverages FastMCP to provide a robust environment for building, configuring, and testing individual Python-based tools.
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    A template and demonstration project for building, testing, and deploying remote MCP servers using FastMCP and uv. It provides a foundational structure for creating MCP-compliant tools that can be hosted publicly and integrated with LLM agents.
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    A Model Context Protocol server built with FastMCP that enables dynamic tool loading and configuration from individual Python files. It provides a flexible framework for automatically discovering, testing, and running tools via Stdio or HTTP transport modes.
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    A transparent proxy that intercepts high-risk tool calls and requires OTP-based human approval before they can be executed. It acts as a configurable circuit breaker between AI agents and target MCP servers to prevent unauthorized or dangerous actions.
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    MIT
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    Enables access to the Pan Card Verification API for validating Indian PAN card details. It provides a dedicated tool for performing PAN verification through a standardized MCP interface.
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    MIT
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    PhysBound is a specialized "Physics Linter" for AI that deterministically validates RF and thermodynamic claims against hard physical limits, preventing hallucinations in engineering workflows.
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    MIT
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    MCP server for business-day arithmetic with country-aware holiday calendars. It offers tools to check, calculate, and list business days and holidays for over 60 countries.
    Last updated
    9
    MIT
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    A personal memory engine and MCP server that stores durable facts in markdown files managed via git, enabling hybrid search (lexical + semantic) through an MCP interface for persistent context across LLM sessions.
    Last updated
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    MIT
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    Sandboxed Python execution with automatic dependency management. Executes Python scripts in isolated environments (bubblewrap or Docker) with PEP 723 inline dependencies, preventing host pollution.
    Last updated
    3
    MIT