Mmcp.market

PageIndex MCP server

by VectifyAI·io.github.VectifyAI/pageindex-mcp·v1.8.2

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

C66/100grade C
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Safety scan
C66/100

full report

Adoption
Growing

391 stars47 downloads/wk

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PageIndex MCP tools (1, 1 write)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • process_documentwrite action

    Upload and process PDF documents from URLs or local files. Supports OCR processing, hierarchical content extraction, and intelligent document analysis. Returns a unique doc_id for subsequent operations. Processing typically takes 0-3 minutes depending on document size (estimate: 2 seconds per page). Supports files up to 100MB.

Public scan report

scanner v0.1.9 · 2026-09-24 · same rubric, same numbers if you re-run it

3 medium
  • Code scan9 source files scanned10/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitylocal package, no credentials required12/15
  • Maintenancelast push 61 days ago12/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year9/10

Findings (3)

  • mediumnpm install lifecycle script presentinstall.script
  • mediumeval / new Function usedexec.eval
    build/index.js: … try { var makeValidate = new Function( "self", "RULES"…
  • mediumnpm install lifecycle script presentinstall.script
    package.json: … "npm run mcpb:build && mcpb pack", "postinstall": "node -e \"try { require('fs').existsSy…
Overall 66/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

What the publisher says

From the PageIndex MCP repository's README, as published. We do not edit it. Read it on GitHub

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 App 🤖: 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.

  1. Go to PageIndex Dashboard to create an API Key
  2. Copy the generated key
  3. Add to your MCP configuration:
{
  "mcpServers": {
    "pageindex": {
      "type": "http",
      "url": "https://api.pageindex.ai/mcp",
      "headers": {
        "Authorization": "Bearer your_api_key"
      }
    }
  }
}

For more details, visit the PageIndex API Dashboard.

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Install directly

Runs npx -y @pageindex/mcp on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add pageindex-mcp -- npx -y @pageindex/mcp
Add to Cursor

PageIndex MCP: common questions

Is PageIndex MCP server safe?
With care: it is graded C, so read the findings first (66/100). Read the PageIndex MCP safety report
How do I install PageIndex MCP?
It runs on your machine. Copy the Claude Code, Claude Desktop or Cursor config from the install section.
Does PageIndex MCP need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is PageIndex MCP maintained?
The last commit was 61 days ago (2026-07-25). The latest release is v1.8.2.
What can I use instead of PageIndex MCP?
Servers from other publishers that do the same job: Basic Memory MCP server, Local Rag MCP server and Google Surf MCP server. Compare all PageIndex MCP alternatives.

Alternatives to PageIndex MCP

Same job from other publishers: the closest match first, then the best rated.

All PageIndex MCP alternatives →
  • Basic Memory
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    C
  • Local Rag
    Easy-to-setup local RAG server with minimal configuration
    A
  • Google Surf
    Web, academic and code search with graph RAG, data lineage, ontology and cross-project schema links.
    B
  • PDF
    Agentic RAG over one PDF or a whole folder: hybrid search, selective page reads, tables, OCR.
    A
  • NVIDIA Elements
    NVIDIA Elements UI design system and agent tools for AI/ML, robotics, and autonomous vehicles.
    A

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