Pdf MCP Server

pdf-mcp

Surgical PDF access for AI agents — search, read, and extract without flooding context.

An MCP server that lets Claude Code and other AI agents search a PDF by meaning or keyword, read only the pages that matter, and cleanly pull out tables, images, and scanned text — even from multi-column and Japanese/Chinese layouts.

mcp-name: io.github.jztan/pdf-mcp

Try it in your browser

See what your AI agent sees →

Drop in any PDF and watch an agent skim it, search it, and read only the pages that matter — using a fraction of the tokens. 100% client-side, no install required.

Why pdf-mcp?

Features

• Hybrid search — find relevant pages with a question, not a page range. Combines BM25 keyword and semantic search via Reciprocal Rank Fusion
• Paginated reading — fetch only the pages your agent needs; large documents don't blow your context window
• OCR — scanned and image-based PDFs are fully readable and searchable via Tesseract
• Structured extraction — tables, embedded images, and table of contents returned as structured data, not text soup
• Vertical-script reading order — Japanese/Chinese tategaki (直排) reconstructed from glyph geometry into correct top-to-bottom, right-to-left order; article segmentation for dense magazine layouts; mojibake filtered
• Persistent cache — SQLite-backed; re-reads are instant and survive server restarts
• Secure URL fetching — HTTPS-only with SSRF protection; local network ranges are blocked

Contents

• Installation
• Quick Start
• Tools
• Example Workflow
• Configuration
• Roadmap
• Contributing
• Security
• License

Installation

pip install pdf-mcp

For semantic search (adds fastembed and numpy, ~67 MB model download on first use):

pip install 'pdf-mcp[semantic]'

For correct reading order on multi-column PDFs (adds pymupdf4llm, which pulls pymupdf_layout/onnxruntime):

pip install 'pdf-mcp[multicolumn]'

Without it, multi-column pages fall back to positional-sort extraction, which can interleave columns.

For Japanese/Chinese/Korean PDFs (recommended — CJK search needs semantic; extraction works without it):

pip install 'pdf-mcp[cjk]'

For OCR on scanned PDFs (requires system Tesseract):

# macOS
brew install tesseract

# Ubuntu/Debian
apt install tesseract-ocr

# Windows — download the installer from:
# https://github.com/UB-Mannheim/tesseract/wiki
# Then add the install directory to your PATH.

Quick Start

Choose your MCP client below to get started:

claude mcp add pdf-mcp -- pdf-mcp

Or add to ~/.claude.json:

{
  "mcpServers": {
    "pdf-mcp": {
      "command": "pdf-mcp"
    }
  }
}

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "pdf-mcp": {
      "command": "pdf-mcp"
    }
  }
}

Config file location:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

Restart Claude Desktop after updating the config.

Requires VS Code 1.101+ with GitHub Copilot.

CLI:

code --add-mcp '{"name":"pdf-mcp","command":"pdf-mcp"}'

Command Palette:

1. Open Command Palette (Cmd/Ctrl+Shift+P)
2. Run MCP: Open User Configuration (global) or MCP: Open Workspace Folder Configuration (project-specific)
3. Add the configuration:

   {
     "servers": {
       "pdf-mcp": {
         "command": "pdf-mcp"
       }
     }
   }
   

4. Save. VS Code will automatically load the server.

Manual: Create .vscode/mcp.json in your workspace:

{
  "servers": {
    "pdf-mcp": {
      "command": "pdf-mcp"
    }
  }
}

codex mcp add pdf-mcp -- pdf-mcp

Or configure manually in ~/.codex/config.toml:

[mcp_servers.pdf-mcp]
command = "pdf-mcp"

Create or edit .kiro/settings/mcp.json in your workspace:

{
  "mcpServers": {
    "pdf-mcp": {
      "command": "pdf-mcp",
      "args": [],
      "disabled": false
    }
  }
}

Save and restart Kiro.

Most MCP clients use a standard configuration format:

{
  "mcpServers": {
    "pdf-mcp": {
      "command": "pdf-mcp"
    }
  }
}

With uvx (for isolated environments):

{
  "mcpServers": {
    "pdf-mcp": {
      "command": "uvx",
      "args": ["pdf-mcp"]
    }
  }
}

Verify Installation

pdf-mcp --help

Tools

The typical pattern: call pdf_info first to plan, then pdf_search to locate — its paragraph excerpts are often enough to answer directly. Use pdf_read_pages or pdf_read_all when you need deeper context.

Example prompts:

"Read the PDF at /path/to/document.pdf"
"Which pages discuss supply chain risks?"
"Find sections about the training process"
"Show me what page 5 looks like"
"OCR pages 3-5 of the scanned PDF"

See docs/tool-reference.md for the complete reference — every parameter, response shape, security contract, and example. For semantic-search model selection, see docs/embedding-models.md.

Example Workflow

For a large document (e.g., a 200-page annual report):

User: "Summarize the risk factors in this annual report"

Agent workflow:
1. pdf_info("report.pdf")
   → 200 pages, TOC shows "Risk Factors" on page 89

2. pdf_search("report.pdf", "risk factors")
   → Matches with structural paragraph excerpts — each excerpt
     is the bullet, paragraph, or heading that matched, not a
     fixed-width window. Often enough to answer directly.

3. If excerpts are sufficient → synthesize answer

4. If more context needed:
   pdf_read_pages("report.pdf", "89-95")
   → Full page text for deeper reading

Configuration

Access control (optional)

Create ~/.config/pdf-mcp/config.toml to restrict which local paths and URL hosts the server will access. The file is optional — if absent, the server is permissive within the built-in SSRF floor (HTTPS-only, blocked private IP ranges).

[paths]
allow = ["~/Documents/**", "/data/pdfs/**"]
deny  = ["~/.ssh/**", "~/.aws/**"]

[urls]
allow = ["*.internal.example.com"]
deny  = ["untrusted.example.com"]

[limits]
max_response_bytes = 200000

The [limits] block caps text-payload byte size on pdf_read_all and section-granularity pdf_search — see docs/response-limits.md. Rules use shell-glob patterns (* matches across path separators). deny wins when both match. Path matching operates on the resolved path after symlink expansion. A malformed config file prevents the server from starting — it never silently falls back to permissive.

Environment variables

# Cache directory (default: ~/.cache/pdf-mcp)
PDF_MCP_CACHE_DIR=/path/to/cache

# Cache TTL in hours (default: 24)
PDF_MCP_CACHE_TTL=48

# Max worker processes for parallel OCR / rendering in pdf_read_pages
# (default: auto = min(cpu_count, pages, 8)). Set to 1 to force sequential.
PDF_MCP_MAX_WORKERS=8

Caching

The server uses SQLite for persistent caching.

Cache location: ~/.cache/pdf-mcp/cache.db

What's cached:

Cache invalidation:

• Automatic when file modification time changes
• Manual via the pdf_cache_clear tool
• TTL: 24 hours (configurable)

Roadmap

See ROADMAP.md for planned features and release history.

Contributing

Contributions are welcome. See docs/contributing.md for setup, checks, the coherence eval harness, and quality-loop guidelines.

Security

Found a vulnerability? See SECURITY.md for the threat model, reporting channel, and expected response timeline. Please do not open a public GitHub issue for unpatched security reports.

License

MIT — see LICENSE.

Links

• pdf-mcp on PyPI
• pdf-mcp on GitHub

Blog posts

Background, benchmarks, and design notes from building pdf-mcp:

Getting started

• How I Built pdf-mcp — The problem with large PDFs in AI agents and a working solution
• How Claude Code Actually Reads PDFs — How AI agents use pdf-mcp tools to read and navigate PDF documents

Search & retrieval

• Semantic vs Keyword Search for AI Agents — Benchmarks and a dual-search routing pattern: FTS5 for exact identifiers, embeddings for natural language
• Hybrid Search vs Query Routing for AI Agents — Why pdf-mcp uses hybrid RRF instead of query routing: benchmarks showing RRF wins across query types
• Section Chunking vs Page Chunking for AI Agents — Why section-aware search delivers full section content in one call while page-mode costs 2–6 extra tool calls per query
• Section-Level RAG: Why BM25 Beat Hybrid Search in My Benchmark — Why pdf-mcp's section-grain search is BM25-only: hybrid RRF caused a 33% lexical regression at section grain, so granularity decides the search technique

Engineering & security

• MCP Server Security: 8 Vulnerabilities — What we found when we audited an MCP server for security holes
• Your LLM Is Free QA for Your MCP Server — Four Payload UX bugs in pdf-mcp that schema tests missed but Claude Desktop surfaced during real use