
PageIndex
OfficialA reasoning-based RAG system that lets LLMs navigate long PDF documents using hierarchical tree structures instead of vector similarity. Works with local and online PDFs up to 1000 pages free.
Reasoning-based RAG system for analyzing long PDF documents
What it does
- Analyze long PDF documents beyond context limits
- Navigate documents through hierarchical tree structures
- Process both local and online PDF files
- Retrieve information using reasoning instead of vector similarity
- Chat with PDFs through MCP-compatible platforms
Best for
About PageIndex
PageIndex is an official MCP server published by vectifyai that provides AI assistants with tools and capabilities via the Model Context Protocol. PageIndex: a reasoning-based RAG system for fast, accurate analysis of long PDFs — extract insights, cite sources, and n It is categorized under ai ml, productivity.
How to install
You can install PageIndex in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.
License
PageIndex is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
PageIndex MCP
If you find this repo useful, please also star our main PageIndex repo ⭐
📘 PageIndex is a vectorless, reasoning-based RAG system that represents documents as hierarchical tree structures. It enables LLMs to navigate and retrieve information through structure and reasoning, not vector similarity — much like a human would retrieve information using a book's index.
🔌 PageIndex MCP exposes this LLM-native, in-context tree index directly to LLMs via MCP, allowing platforms like Claude, Cursor, and other MCP-compatible agents or LLMs to reason over document structure and retrieve the right information — without vector databases.
Want to chat with long PDFs but hit context limit reached errors? Add your file to PageIndex to seamlessly chat with long PDFs on any agent/LLM platforms.
✨ Chat to long PDFs the human-like, reasoning-based way ✨
- Support local and online PDFs
- Free 1000 pages
- Unlimited conversations
For more information, visit the PageIndex MCP page.
💡 Looking for a fully hosted experience? Try PageIndex Chat 🤖: a human-like document analyst that lets you chat with long PDFs using the same agentic, reasoning-based workflow as PageIndex MCP.
What is PageIndex?
PageIndex is a vectorless, reasoning-based RAG system that generates hierarchical tree structures of documents and uses multi-step reasoning and tree search to retrieve information like a human expert would. It has the following key properties:
- Higher Accuracy: Relevance beyond similarity
- Better Transparency: Clear reasoning trajectory with traceable search paths
- Like A Human: Retrieve information like a human expert navigates documents
- No Vector DB: No extra infrastructure overhead
- No Chunking: Preserve full document context and structure
- No Top-K: Retrieve all relevant passages automatically
PageIndex MCP Setup
For Developers
Connect PageIndex to your agent framework or AI SDK via MCP. Works with Claude Agent SDK, Vercel AI SDK, OpenAI Agents SDK, LangChain, and any MCP-compatible client. Simple API Key authentication — no OAuth flow required.
- Go to PageIndex Dashboard to create an API Key
- Copy the generated key
- Add to your MCP configuration:
{
"mcpServers": {
"pageindex": {
"type": "http",
"url": "https://api.pageindex.ai/mcp",
"headers": {
"Authorization": "Bearer your_api_key"
}
}
}
}
For more details, visit the PageIndex API Dashboard.
For PageIndex Chat Users
If you already have a PageIndex Chat account, you can connect your MCP client directly via OAuth.
Claude Desktop — One-Click Install:
Download the .mcpb file from Releases and double-click to install. OAuth authentication is handled automatically.
Other MCP Clients:
{
"mcpServers": {
"pageindex": {
"type": "http",
"url": "https://chat.pageindex.ai/mcp"
}
}
}
Local MCP Server (with local PDF upload):
If you need to upload local PDF files, you can run the local MCP server (requires Node.js ≥18.0.0):
{
"mcpServers": {
"pageindex": {
"command": "npx",
"args": ["-y", "@pageindex/mcp"]
}
}
}
For more details, visit PageIndex Chat.
Related Links
License
This project is licensed under the terms of the MIT open source license. Please refer to MIT for the full terms.
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