<div align="center">
<a href="https://pageindex.ai/mcp">
<img src="https://docs.pageindex.ai/images/general/mcp_banner.jpg">
</a>
</div>
# PageIndex MCP
> If you find this repo useful, please also star our **[main PageIndex repo](https://github.com/VectifyAI/PageIndex)** ⭐
[](https://github.com/VectifyAI/PageIndex) [](https://pageindex.ai/mcp) [](https://vectify.ai/pageindex)
📘 [**PageIndex**](https://github.com/VectifyAI/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**](https://pageindex.ai/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](https://pageindex.ai/mcp) page.
💡 Looking for a fully hosted experience? Try [**PageIndex Chat**](https://chat.pageindex.ai) 🤖: a human-like document analyst that lets you chat with long PDFs using the same agentic, reasoning-based workflow as PageIndex MCP.
<p align="center">
<a href="https://pageindex.ai/mcp">
<img src="https://github.com/user-attachments/assets/d807d506-131d-4c7b-837c-96ab1adb2271">
</a>
</p>
# What is PageIndex?
<div align="center">
<a href="https://pageindex.ai/mcp">
<img src="https://docs.pageindex.ai/images/cookbook/vectorless-rag.png" width="70%">
</a>
</div>
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
See [PageIndex MCP](https://pageindex.ai/mcp) for full video guidances.
### 1. For Claude Desktop (Recommended)
**One-Click Installation with Desktop Extension (MCPB):**
1. Download the latest `.mcpb` file from [Releases](https://github.com/VectifyAI/pageindex-mcp/releases)
2. Double-click the `.mcpb` file to install automatically in Claude Desktop
3. The OAuth authentication will be handled automatically when you first use the extension
> **Note**: Claude Desktop Extensions now use the `.mcpb` (MCP Bundle) file extension. Existing `.dxt` extensions will continue to work, but we recommend using `.mcpb` for new installations.
This is the easiest way to get started with PageIndex's reasoning-based RAG capabilities.
### 2. For Other MCP-Compatible Clients
#### Option 1: Local MCP Server (with local PDF upload)
**Requirements:** Node.js ≥18.0.0
Add to your MCP configuration:
```json
{
"mcpServers": {
"pageindex": {
"command": "npx",
"args": ["-y", "@pageindex/mcp"]
}
}
}
```
> **Note**: This local server provides full PDF upload capabilities and handles all authentication automatically.
#### Option 2: Direct Connection to PageIndex
Connect directly to the PageIndex OAuth-enabled MCP server:
```json
{
"mcpServers": {
"pageindex": {
"type": "http",
"url": "https://chat.pageindex.ai/mcp"
}
}
}
```
**Using API Key Authentication (for programmatic use or clients without OAuth support):**
1. Go to [PageIndex Chat API Keys](https://chat.pageindex.ai/chat#settings/api-keys)
2. Click **Create Key** and copy the generated key (format: `pi_xxxxx...`)
3. Add the `Authorization` header to your configuration:
```json
{
"mcpServers": {
"pageindex": {
"type": "http",
"url": "https://chat.pageindex.ai/mcp",
"headers": {
"Authorization": "Bearer pi_your_api_key_here"
}
}
}
}
```
> **Note**: The full API Key is only shown once at creation. Store it securely.
**For clients that don't support HTTP MCP servers:**
If your MCP client doesn't support HTTP servers directly, you can use [mcp-remote](https://github.com/geelen/mcp-remote) as a bridge:
```json
{
"mcpServers": {
"pageindex": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://chat.pageindex.ai/mcp"]
}
}
}
```
> **Note**: Option 1 provides local PDF upload capabilities, while Option 2 only supports PDF processing via URLs (no local file uploads).
# Related Links
[](https://vectify.ai/pageindex)
[](https://github.com/VectifyAI/PageIndex)
## License
This project is licensed under the terms of the MIT open source license. Please refer to [MIT](./LICENSE) for the full terms.
