PDF Reader MCP Server
A Model Context Protocol (MCP) server that provides tools for reading and extracting text from PDF files, supporting both local files and URLs.
Author
Philip Van de WalkerEmail: philip.vandewalker@gmail.comGitHub: https://github.com/trafflux
Features
- Read text content from local PDF files
- Read text content from PDF URLs
- Error handling for corrupt or invalid PDFs
- Volume mounting for accessing local PDFs
- Auto-detection of PDF encoding
- Standardized JSON output format
Installation
- Clone the repository:
- Build the Docker image:
Usage
Running the Server
To run the server with access to local PDF files:
Replace
/path/to/pdfs with the actual path to your PDF files directory.If not using local PDF files:
MCP Configuration
Add to your MCP settings configuration:
Without local file PDF files:
Available Tools
read_local_pdf
read_pdf_url
Error Handling
The server handles various error cases with clear error messages:
- Invalid or corrupt PDF files
- Missing files
- Failed URL requests
- Permission issues
- Network connectivity problems
Error responses follow the format:
Dependencies
- Python 3.11+
- PyPDF2: PDF parsing and text extraction
- requests: HTTP client for fetching PDFs from URLs
- MCP SDK: Model Context Protocol implementation
Project Structure
License
Copyright 2025 Philip Van de Walker
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Contact
For questions, issues, or contributions, please contact Philip Van de Walker:
- Email: philip.vandewalker@gmail.com
- GitHub: https://github.com/trafflux
PDF Reader MCP Server
A Model Context Protocol (MCP) server that provides tools for reading and extracting text from PDF files, supporting both local files and URLs.
Author
Philip Van de WalkerEmail: philip.vandewalker@gmail.comGitHub: https://github.com/trafflux
Features
- Read text content from local PDF files
- Read text content from PDF URLs
- Error handling for corrupt or invalid PDFs
- Volume mounting for accessing local PDFs
- Auto-detection of PDF encoding
- Standardized JSON output format
Installation
- Clone the repository:
- Build the Docker image:
Usage
Running the Server
To run the server with access to local PDF files:
Replace
/path/to/pdfs with the actual path to your PDF files directory.If not using local PDF files:
MCP Configuration
Add to your MCP settings configuration:
Without local file PDF files:
Available Tools
read_local_pdf
read_pdf_url
Error Handling
The server handles various error cases with clear error messages:
- Invalid or corrupt PDF files
- Missing files
- Failed URL requests
- Permission issues
- Network connectivity problems
Error responses follow the format:
Dependencies
- Python 3.11+
- PyPDF2: PDF parsing and text extraction
- requests: HTTP client for fetching PDFs from URLs
- MCP SDK: Model Context Protocol implementation
Project Structure
License
Copyright 2025 Philip Van de Walker
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Contact
For questions, issues, or contributions, please contact Philip Van de Walker:
- Email: philip.vandewalker@gmail.com
- GitHub: https://github.com/trafflux