Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@PageIndex MCPsummarize the key findings from the quarterly report PDF I uploaded"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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:
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:
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):
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.