Obsidian Pdf Evidence
O

Obsidian Pdf Evidence

An Obsidian plugin that provides PDF content and knowledge base access to AI agents through the MCP protocol, supporting functions such as PDF text extraction, fuzzy search, reference link generation, knowledge base file reading and writing, and Dataview queries.
2 points
4.3K

What is Obsidian PDF Evidence?

Obsidian PDF Evidence is an Obsidian plugin that acts as a bridge between AI assistants and your knowledge base. It allows AI (such as Claude, OpenCode, etc.) to directly access the content of PDF files opened in Obsidian and provide evidence-supported answers based on this content. The plugin automatically extracts PDF text, generates precise reference links, and displays the AI's answers in the Obsidian sidebar.

How to use Obsidian PDF Evidence?

The usage is divided into three steps: 1) Install and enable the plugin in Obsidian; 2) Configure the MCP connection in the AI client (such as Claude Desktop); 3) Open a PDF file in Obsidian and then ask questions to the AI. The AI will read the PDF content, provide answers with reference evidence, and display the results in the AI answer panel of Obsidian.

Use cases

It is most suitable for scenarios such as academic research, paper reading, literature review, and learning note organization. When you need to quickly understand complex papers, find specific information, or conduct comprehensive analysis based on multiple literatures, this tool can significantly improve efficiency.

Main features

PDF text extraction
Automatically extract text content from PDF files opened in Obsidian and cache it for AI access. It supports two modes: chunk reading and full-text reading.
Fuzzy search and PDF++ citations
Find text fragments in the PDF and generate clickable PDF++ reference links. Use the Levenshtein distance algorithm for fuzzy matching, so that the correct position can be found even if there are minor differences in the text.
Knowledge base access
AI can read and write Markdown files, search the content of the knowledge base, and manage tags. It supports viewing all tags and their usage frequencies.
Dataview integration
Run Dataview queries through the API, allowing AI to access structured data in your knowledge base, such as task lists and literature databases.
AI answer panel
Display the AI's answers in the Obsidian sidebar. All internal links are clickable, providing a natural reading experience. Users can copy the original Markdown or close the panel.
Professor Agent preset
Provide a specially optimized system prompt (Professor Agent) to ensure that the AI correctly uses the citation format, answers questions based on evidence, and follows best practices.
Advantages
Evidence-driven answers: All factual statements are supported by PDF citations, avoiding AI hallucinations.
Seamless integration: Use directly in the Obsidian workflow without switching applications.
Precise citations: Generate PDF++ links that can be clicked to jump to the exact position in the PDF.
Multi-tool support: Compatible with AI clients that support the MCP protocol, such as Claude Desktop and OpenCode.
User-friendly: Non-technical users can easily configure and use it.
Open source and free: Licensed under the MIT license, allowing free use and modification.
Limitations
Requires Obsidian: Must use Obsidian as a knowledge management tool.
Only supports PDF: Currently mainly targets PDF files, with limited support for other formats.
Local operation: Requires a local HTTP server, which may involve port configuration.
Performance dependence: Text extraction and processing of large PDFs may take time.
AI client compatibility: Requires the AI client to support the MCP protocol.

How to use

Install the plugin
Install the Obsidian PDF Evidence plugin in Obsidian. You can install it through the community plugin market or build it from the source code.
Configure the plugin
Enable the plugin in the Obsidian settings and configure the server port (default 27123). Use the 'Copy MCP bridge configuration' button to get the configuration information.
Configure the AI client
Add the MCP server configuration in Claude Desktop or OpenCode. Paste the configuration provided by the plugin into the corresponding configuration file.
Use the Professor Agent
Create a project in Claude Desktop and add the Professor Agent prompt as a custom instruction. Or configure the Professor Agent in OpenCode.
Start using
Open a PDF file in Obsidian and ask questions to the AI. The AI will read the PDF content and provide answers with reference evidence, and the results will be displayed in the sidebar.

Usage examples

Quick understanding of a paper
You have just downloaded a complex academic paper and need to quickly understand its main contributions and methods.
Precise information search
You remember seeing a specific experimental data in a paper but are not sure of the exact location.
Comparison of multiple literatures
You are writing a literature review and need to compare the similarities and differences of the methods in multiple papers.
Automatic tag management
You want to add appropriate tags to the papers you read for subsequent retrieval.

Frequently Asked Questions

Do I need programming knowledge to use this plugin?
Which AI clients are supported?
What are PDF++ reference links?
What if port 27123 is occupied?
Can the AI access all my notes?
Does it support scanned PDFs (image format)?
Is the Professor Agent prompt necessary?

Related resources

GitHub repository
Plugin source code, issue tracking, and latest version
Obsidian official forum
Community discussions, usage tips, and problem help
MCP protocol documentation
Official documentation and specifications of the Model Context Protocol
Claude Desktop download
Claude Desktop client download page
OpenCode project
OpenCode AI development platform
Korean README
Korean version of the usage instructions

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "obsidian-pdf-evidence": {
      "command": "node",
      "args": ["{path-to-vault}/.obsidian/plugins/obsidian-pdf-evidence/bridge/bridge.mjs"],
      "env": {
        "PDF_EVIDENCE_BASE_URL": "http://127.0.0.1:27123"
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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