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"A tool or assistant to explore and debug my codebase" matching MCP servers:

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    An MCP server for dataset exploration and analysis, enabling LLM clients to perform summary, correlation, distribution, missing value analysis, data cleaning, and statistical tests directly on CSV files.
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    An intelligent debugging assistant that automates the debugging process by analyzing bugs, injecting HTTP-based debug logs into code across multiple environments (browser, Node.js, mobile, etc.), and iteratively fixing issues based on real-time feedback.
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    MIT
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    Structures debugging processes into a persistent knowledge graph, enabling problem decomposition, hypothesis testing, and reusable solution discovery.
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    MIT
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    A Model Context Protocol server that provides a scratchpad tool for LLMs to organize thoughts, take notes, and plan approaches to complex problems.
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    MIT
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    chrome-debug-mcp is an asynchronous Rust-based Model Context Protocol (MCP) server that allows AI agents and Large Language Models to natively debug Chromium-based browsers via the Chrome DevTools Protocol (CDP).
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    MIT
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    A read-only MCP server that lets a Claude chat explore your local repository and answer questions about it, returning synthesized answers with file:line references.
    3
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    MIT
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    A local-first MCP server that indexes code repositories and enables AI assistants to search, fetch, and navigate code using BM25 hybrid retrieval, supporting common languages and tools like Codex and ChatGPT.
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    MIT
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    Provides AI assistants with real-time visibility into your codebase's internal libraries, team patterns, naming conventions, and usage frequencies to generate code that matches your team's actual practices.
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    Elastic 2.0
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    Zero-config MCP server that connects local codebases to AI assistants, providing secure project tree, regex search, file reading, and tech stack tools locally.
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    MIT
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    A PDF debugging MCP server that inspects low-level PDF structure, including indirect objects, content streams, page trees, and resources.
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    Bridges web browsers and Claude Code for seamless debugging workflows by receiving debug data from browser widgets and exposing it to Claude Code via MCP protocol.
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    Enables AI tools to perform full-featured embedded microcontroller debugging via pyOCD and CMSIS-DAP probes, including probe management, flashing, breakpoints, register/memory access, fault analysis, and RTT communication.
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    MIT