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NavamAI logo
NavamAI
✓ verifiedFree

CLI-based personal AI that runs 15+ LLMs from your terminal and pairs with Markdown tools like Obsidian and VS Code.

991 visits/mo
Gemini Code Assist logo
Gemini Code Assist
✓ verifiedFreemium

Google's AI coding assistant for code completion, generation, chat and review across IDEs and GitHub.

559K visits/mo
Pieces logo
Pieces
✓ verifiedFreemium

An on-device developer memory tool that auto-captures code, docs and context across apps so engineers can search and reuse it later.

170K visits/mo
Continue logo
Continue
✓ verifiedFreemium

Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.

775K visits/mo
Pricing

No public pricing

No public pricing

No public pricing

No public pricing

Core features
  • Terminal/CLI interface for prompting LLMs
  • Access to 15 models across 7 providers
  • Markdown workflow integration (Obsidian, VS Code, MkDocs)
  • Situational web-app generation and local run
  • Web scraping/content extraction (gather)
  • Vision-model support for images
  • Configurable prompt templates and intents
  • AI code completion and suggestions
  • Natural-language code generation
  • In-IDE chat assistance
  • AI code review
  • IDE integrations (VS Code, JetBrains, etc.)
  • GitHub integration
  • Automatic capture of code, docs and context across apps
  • Long-term memory engine for time-based search of past work
  • One-click save, search and AI-tagging of code snippets
  • Local, on-device processing with optional cloud sync
  • Plugin support for browsers and IDEs like VS Code
  • MCP integration with external LLMs for contextual answers
  • Open-source AI code assistant
  • Customizable autocomplete
  • In-editor AI chat
  • Community-built coding agent
Use cases
  • Prompt and compare multiple LLMs from the terminal
  • Generate and run small web apps without setup
  • Automate Markdown document workflows
  • Extract structured content from text and webpages
  • Speeding up coding with AI completions
  • Generating code from plain-language prompts
  • Getting in-editor help and explanations
  • Reviewing pull requests with AI
  • Understanding unfamiliar codebases
  • Recalling code snippets and context from past coding sessions
  • Feeding accurate personal context into AI coding assistants
  • Keeping research notes and links without manual bookmarking
  • Preserving shared context across team collaboration tools
  • Get AI code completions while coding
  • Ask questions about code in the editor
  • Build on an open-source coding-agent foundation
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