# Pageindex Mcp

> Reasoning-based RAG system for chatting with long PDFs. Supports local and online files.

- **Type:** MCP server
- **Install:** `agentstack add mcp-vectifyai-pageindex-mcp`
- **Verified:** Pending review
- **Seller:** [VectifyAI](https://agentstack.voostack.com/s/vectifyai)
- **Installs:** 0
- **Latest version:** 1.6.2
- **License:** MIT
- **Upstream author:** [VectifyAI](https://github.com/VectifyAI)
- **Source:** https://github.com/VectifyAI/pageindex-mcp
- **Website:** https://pageindex.ai/mcp

## Install

```sh
agentstack add mcp-vectifyai-pageindex-mcp
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# 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.

  
    
  

# 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](https://github.com/anthropics/claude-agent-sdk-python), [Vercel AI SDK](https://ai-sdk.dev/docs/ai-sdk-core/mcp-tools), [OpenAI Agents SDK](https://openai.github.io/openai-agents-python/mcp/), [LangChain](https://github.com/langchain-ai/langchain-mcp-adapters), and any MCP-compatible client. Simple API Key authentication — no OAuth flow required.

1. Go to [PageIndex Dashboard](https://dash.pageindex.ai/api-keys) to create an API Key
2. Copy the generated key
3. Add to your MCP configuration:

```json
{
  "mcpServers": {
    "pageindex": {
      "type": "http",
      "url": "https://api.pageindex.ai/mcp",
      "headers": {
        "Authorization": "Bearer your_api_key"
      }
    }
  }
}
```

For more details, visit the [PageIndex API Dashboard](https://dash.pageindex.ai).

### For PageIndex Chat Users

If you already have a [PageIndex Chat](https://chat.pageindex.ai) account, you can connect your MCP client directly via OAuth.

**Claude Desktop — One-Click Install:**

Download the `.mcpb` file from [Releases](https://github.com/VectifyAI/pageindex-mcp/releases) and double-click to install. OAuth authentication is handled automatically.

**Other MCP Clients:**

```json
{
  "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):

```json
{
  "mcpServers": {
    "pageindex": {
      "command": "npx",
      "args": ["-y", "@pageindex/mcp"]
    }
  }
}
```

For more details, visit [PageIndex Chat](https://chat.pageindex.ai).

# 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.

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [VectifyAI](https://github.com/VectifyAI)
- **Source:** [VectifyAI/pageindex-mcp](https://github.com/VectifyAI/pageindex-mcp)
- **License:** MIT
- **Homepage:** https://pageindex.ai/mcp

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Versions

- **1.6.2** — security scan: pending review — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/mcp-vectifyai-pageindex-mcp
- Seller: https://agentstack.voostack.com/s/vectifyai
- Browse the marketplace: https://agentstack.voostack.com/browse

---
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