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Code Pathfinder

Created at 2 days ago

by shivasurya

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Code Pathfinder's MCP Server provides AI coding assistants like Claude Code with deep semantic understanding of codebases through call graph analysis, symbol search, and dependency tracking. It enables developers to ask natural language questions like "who calls this function?" instead of manually using grep or searching code. The tool runs 100% locally (your code never leaves your machine), is free and open-source under AGPL-3.0, and installs in under 5 minutes. [codepathfinder](https://codepathfinder.dev/mcp)

Categories

developer-tools

Tags

static-analysis

security scanning

static code analysis

code analysis

sast

code intelligence

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Code Pathfinder

What is Code Pathfinder?

Code Pathfinder is an AI-powered coding assistant that provides deep semantic understanding of codebases through call graph analysis, symbol search, and dependency tracking, enabling developers to ask natural language questions about their code.

How to use Code Pathfinder?

To use Code Pathfinder, install it locally using Homebrew, pip, Chocolatey, or Docker, and configure it with your AI coding assistant. You can then query your codebase using natural language.

Key features of Code Pathfinder?

  • Local execution ensuring code privacy
  • Natural language queries for code analysis
  • Six specialized analysis tools including project statistics and symbol search
  • Multi-project support for complex architectures

Use cases of Code Pathfinder?

  1. Security vulnerability analysis to trace user input flows.
  2. Codebase onboarding for new team members.
  3. Refactoring support to assess impact on function calls.
  4. Dependency analysis for managing technical debt.

FAQ from Code Pathfinder?

  • Is Code Pathfinder free to use?

Yes! Code Pathfinder is free and open-source under AGPL-3.0.

  • Does it support multiple programming languages?

Currently supports Python, with plans for JavaScript, TypeScript, Go, and Java.

  • How does it ensure code privacy?

All analysis runs locally on your machine, ensuring your code never leaves your environment.

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