PageIndex

# 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.