The mcp-pdf-tools server enables AI assistants to read, search, and analyze text-based PDF documents through the Model Context Protocol.
Core Capabilities:
Extract metadata - Access document information including title, author, page count, text length, creator, and producer
Extract text content - Get all text from a PDF or specific page ranges, with configurable character limits (default 50,000 chars)
Search within documents - Find text matches with case-insensitive search, returning surrounding context, line numbers, and configurable result limits (default 20 matches)
Analyze word statistics - Generate word frequency reports showing total word count and most common words (3+ characters, default top 20)
Requirements:
Absolute file path to the PDF required
Only works with text-based PDFs (no OCR for scanned documents)
Files loaded entirely into memory
Use Cases: Summarizing documents, searching contracts for specific terms, analyzing research papers, extracting specific sections, and retrieving quick metadata without opening files.
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., "@mcp-pdf-toolsSummarize the key points in /documents/annual-report.pdf"
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.
mcp-pdf-tools
MCP server for extracting text, searching, and analyzing PDF files
Give Claude (or any MCP client) the ability to read, search, and analyze PDF documents.
What is this?
mcp-pdf-tools is a Model Context Protocol server that gives AI assistants the ability to work with PDF files. Point it at any text-based PDF and your assistant can extract content, search for specific text, pull metadata, and analyze word usage — all without leaving the conversation.
Quick Start
Claude Desktop
Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):
Claude Code
Other MCP Clients
The server communicates over stdio using the MCP protocol.
Tools
pdf_info
Get metadata and statistics about a PDF file.
Parameter | Type | Required | Description |
| string | Yes | Absolute path to the PDF file |
Returns: Title, author, page count, text length, creator, and producer information.
pdf_extract_text
Extract all text content from a PDF file.
Parameter | Type | Required | Default | Description |
| string | Yes | — | Absolute path to the PDF file |
| number | No | 50000 | Maximum characters to return (truncates with notice) |
Returns: Full text content of the PDF, prefixed with page count.
pdf_extract_pages
Extract text from a specific page range.
Parameter | Type | Required | Description |
| string | Yes | Absolute path to the PDF file |
| number | Yes | Start page (1-indexed) |
| number | Yes | End page (inclusive) |
Returns: Text content from the specified page range.
pdf_search
Search for text within a PDF file, returning matches with surrounding context.
Parameter | Type | Required | Default | Description |
| string | Yes | — | Absolute path to the PDF file |
| string | Yes | — | Text to search for (case-insensitive) |
| number | No | 20 | Maximum number of matches to return |
Returns: List of matches with line numbers and surrounding context lines.
pdf_word_stats
Get word count and top word frequencies from a PDF.
Parameter | Type | Required | Default | Description |
| string | Yes | — | Absolute path to the PDF file |
| number | No | 20 | Number of top words to include |
Returns: Total word count, page count, and a ranked list of the most frequent words (3+ characters).
Example Conversations
Summarizing a report
You: Summarize the key points in /documents/quarterly-report.pdf
Claude: (uses
This is a 24-page quarterly report covering Q4 2025. The key points are...
Searching a contract
You: Does the NDA in /legal/nda-acme.pdf mention anything about a non-compete?
Claude: (uses
Yes — I found 3 mentions of "non-compete" in the document. On line 47, there's a clause stating...
Analyzing word usage
You: What are the most discussed topics in /research/paper.pdf?
Claude: (uses
The paper is 8,400 words across 12 pages. The most frequent terms are "neural" (47 occurrences), "training" (38), and "optimization" (29), suggesting the paper focuses heavily on...
Limitations
Be aware of these current constraints:
Text-based PDFs only — Scanned or image-based PDFs will return empty text. No OCR support (yet).
Page extraction is approximate — Page boundaries are detected heuristically. Extracted page ranges may not align perfectly with the visual pages in your PDF viewer.
No table extraction — Tabular data in PDFs may not preserve its structure in the extracted text.
Full file loaded into memory — Very large PDFs may be slow to process.
No merge or split — This tool reads PDFs; it does not modify, merge, or split them.
Development
License
MIT