Pageindex MCP

What pageindex-mcp does

pageindex-mcp gives MCP clients tools for loading and investigating PDF documents through PageIndex. Documents are represented as hierarchical trees, allowing an agent to navigate folders, sections, and page references before reading relevant content. The approach is designed for reasoning-based retrieval rather than vector similarity, document chunking, or a fixed top-k result set.

It accepts PDF files from URLs and, when run locally, local PDF files. Processing includes OCR, hierarchical content extraction, and document analysis. A processed document receives a unique doc_id, which is used by later operations. Files can be up to 100 MB, and processing commonly takes between zero and three minutes, with an estimate of about two seconds per page.

How it works

A reliable retrieval sequence starts with get_folder_structure() to map the available document hierarchy. The agent can then use browse_documents() at the root or within a folder, optionally sorting by relevance with a query. search_documents() is intended as a fallback when relevance-based browsing misses a document that should match a precise term, acronym, or filename fragment.

For an individual document, get_document() reports processing state and metadata. Once the document is ready, get_document_structure() exposes its outline, section headers, and page references. Documents longer than 20 pages should be handled through the outline first, with pagination used for large structures. The agent can then request narrow page ranges through get_page_content() instead of loading the entire file at once.

Page content may include paths for embedded images or rendered page images. Passing one of those paths to get_document_image() returns an MCP image content block, which is useful for scanned pages and layouts whose meaning depends on visual presentation.

Setup and configuration

For hosted use, create an API key in the PageIndex dashboard and configure an HTTP MCP connection to https://api.pageindex.ai/mcp with an Authorization: Bearer ... header. The setup uses API-key authentication and does not require an OAuth flow.

PageIndex App users can connect through https://app.pageindex.ai/mcp; Claude Desktop also has a one-click option using the .mcpb package from the project’s releases. OAuth is handled for that App-based connection.

To upload local PDFs, run the local MCP package through npx with Node.js 18 or newer:

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

The hosted endpoint can be used from agent frameworks and SDKs that support MCP, including the Claude Agent SDK, Vercel AI SDK, OpenAI Agents SDK, and LangChain MCP adapters.

Tools and capabilities

• process_document: Upload and analyze a PDF from a URL or local path.
• get_folder_structure: Display the document hierarchy as a tree.
• browse_documents: Navigate folders or retrieve documents by relevance.
• search_documents: Perform keyword-based fallback searches with relevance scores.
• get_document: Check processing status and metadata.
• get_document_structure: Read section outlines and page references.
• get_page_content: Extract selected page ranges.
• get_document_image: Return embedded or rendered page images.
• remove_document: Permanently delete explicitly confirmed documents and their associated data.

Removal is irreversible, so clients should require explicit confirmation and inspect each returned per-document result.