PDF Reader
This MCP server implementation provides a PDF reading service for AI assistants. Developed by Philip Van de Walker, it utilizes PyPDF2 for PDF processing and is containerized using Docker for easy deployment. The server is designed to work with Python 3.11 and integrates the Model Context Protocol SDK directly from GitHub. It offers a simple interface for accessing and extracting information from PDF files, with the ability to mount local PDF directories for processing. The implementation focuses on efficiency and ease of use, making it suitable for AI applications that require text extraction or analysis from PDF documents in various domains such as document management, information retrieval, or content summarization.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- version-control
- Source
- PulseMCP
- Repository
- github.com/trafflux/pdf-reader-mcp
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve PDF Reader from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.