GNO vs Khoj

Verdict: Both offer semantic search over local documents with AI chat. Khoj is a full-featured personal AI platform with cloud LLM support, mobile access, and custom agents. GNO is CLI-first with MCP integration and REST API. Choose Khoj for multi-platform personal assistant, GNO for developer workflows and AI agent integration.

Both tools provide semantic search for local documents with AI-powered RAG features. Here’s how they compare.

Get Started

# GNO
bun install -g @gmickel/gno
gno init ~/notes --name notes && gno index

# Khoj (pip)
pip install 'khoj[local]'
USE_EMBEDDED_DB="true" khoj --anonymous-mode

# Khoj (Docker)
mkdir ~/.khoj && cd ~/.khoj
wget https://raw.githubusercontent.com/khoj-ai/khoj/master/docker-compose.yml
docker-compose up

Quick Summary

Aspect GNO Khoj
Best for Developers, AI agents Personal AI assistant
Unique strength CLI, MCP, REST API Multi-platform, custom agents
Stack Bun/TypeScript Python/TypeScript
License MIT AGPL-3.0

Feature Comparison

Feature GNO Khoj
Search Modes BM25, Vector, Hybrid Vector (semantic)
Reranking ✓ Cross-encoder ✓ Cross-encoder
AI Answers (RAG)
CLI ✓ Full-featured ✓ Server command only
Web UI gno serve ✓ Gradio-based
REST API
MCP Support ✓ 10+ targets
Query Expansion ✓ LLM-powered
HyDE
Model Presets ✓ slim/balanced/quality
Search Depth ✓ fast/balanced/thorough
Tab Completion ✓ bash/zsh/fish

File Format Support

Format GNO Khoj
Markdown
PDF
DOCX
XLSX
PPTX
Org-mode
Notion ✓ (integration)
Images

LLM Support

Provider GNO Khoj
Local (llama.cpp) ✓ Built-in
Ollama
OpenAI
Anthropic
Google Gemini
Mistral

Database & Infrastructure

Aspect GNO Khoj
Database SQLite (embedded) PostgreSQL + pgvector
Setup Single binary Multi-container (Docker)
Services 1 4-5 (db, server, sandbox, search)

GNO Advantages

CLI-first design: Full-featured command line for scripting and automation.

gno query "authentication flow" --format json | jq '.results[0]'

MCP integration: One-command setup for Claude, Cursor, Windsurf, and more.

gno mcp install --target cursor

REST API: Programmatic access for custom integrations.

gno serve  # http://localhost:3000/api

Search refinement: Query expansion, HyDE, BM25 hybrid, and configurable search depth.

gno ask "how does caching work" --depth thorough --answer

Zero infrastructure: SQLite embedded, no separate database server.

Skills: Native integration for Claude Code, Codex, OpenCode.

MIT License: Permissive licensing for commercial use.

Khoj Advantages

Multi-platform access: Browser, Obsidian, Emacs, Desktop, Phone, WhatsApp integration.

Custom agents: Create agents with tunable personality, tools, and knowledge bases.

Cloud LLM support: Works with OpenAI, Anthropic, Google, Mistral out of the box.

Research mode: Experimental /research command for automated research workflows.

Cloud option: app.khoj.dev available for zero-setup usage.

Image generation: Built-in text-to-image and text-to-speech capabilities.

Notion integration: Direct sync with Notion workspaces.

When to Choose GNO

  • You want CLI access for scripting and automation
  • You need REST API for custom integrations
  • You’re integrating with AI coding assistants (Claude, Cursor, Windsurf)
  • You want MCP support for agent workflows
  • You prefer local-first, no cloud dependencies
  • You need fine-grained search control (BM25 hybrid, depth, expansion, HyDE)
  • You want simple SQLite setup, no PostgreSQL
  • You need MIT licensing for commercial projects

When to Choose Khoj

  • You want multi-platform access (mobile, WhatsApp, Obsidian, Emacs)
  • You need to use cloud LLMs (OpenAI, Anthropic, Google)
  • You want custom AI agents with different personalities
  • You use Notion and want direct integration
  • You prefer a managed cloud option (app.khoj.dev)
  • You need image/audio generation features
  • You work with Org-mode files

Architecture Comparison

GNO: TypeScript/Bun, SQLite + node-llama-cpp, designed for CLI and MCP integration. Single-user, local-first, zero external dependencies.

Khoj: Python/TypeScript hybrid, PostgreSQL + pgvector, designed as a personal AI platform. Supports cloud or self-hosted, multi-user capable, requires Docker for full features.