Spy Search is a self-hosted agentic search framework that orchestrates multiple AI agents — Planner, Searcher, and Reporter — to deliver fast, accurate answers and long-form research reports from live web content. It supports OpenAI, DeepSeek, Gemini, Grok, Anthropic, and Ollama out of the box, and costs nothing beyond your LLM API usage.Documentation Index
Fetch the complete documentation index at: https://mintlify.com/JasonHonKL/spy-search/llms.txt
Use this file to discover all available pages before exploring further.
Quickstart
Get Spy Search running locally in under 5 minutes with a working configuration.
Docker Setup
Deploy the full stack — backend and frontend — with a single Docker Compose command.
Configuration
Learn how to configure your LLM provider, model, and agents via config.json.
API Reference
Explore all REST endpoints for search, reports, file management, and more.
What Spy Search Does
Spy Search routes your queries through a coordinated pipeline of AI agents. The Planner decomposes the task, the Searcher retrieves live web content via DuckDuckGo, and the Reporter synthesizes a coherent response or long-form report — all in one request.Search Modes
Quick search, deep search, and academic arXiv search modes.
Report Generation
Generate ~2000-word research reports from live sources.
Local RAG
Query your own documents with ChromaDB vector search.
Get Started in 3 Steps
Clone and configure
Clone the repository and copy the example config to
config.json. Set your LLM provider, model, and desired agents.Spy Search v0.3 is the current stable release. Check the Roadmap for planned features including MCP support, Google API integration, and multi-site search.