PDF Search
About
Built for Zed to enable semantic searching of PDF documents using a Qdrant vector database and OpenAI embeddings.
Details
- Author
- freespirit
- Repository
- freespirit/pdfsearch-zed
- GitHub stars
- 2
- Categories
- Design, Workplace, File Management, AI, Search, Frontend, Database, API
- Tags
- #integration
Jump to
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
PDF SearchCommand (node, npx, python, etc.)npxArguments-
Argument 1
-y -
Argument 2
@highlight/mcp-server
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
-
Argument 1
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
1. Open Zed's AI Assistant panel
2. Type /pdfsearch followed by your search query
3. The extension will search the PDF and add relevant sections to the AI
Assistant's context
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"pdf search": {
"env": {},
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}
}
}Linux
{
"env": [],
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}Macos
{
"env": [],
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}Windows
{
"env": [],
"args": [
"/c",
"npx",
"-y",
"@highlight/mcp-server"
],
"command": "cmd"
}PDF Search for Zed
A document search extension for Zed that lets you semantically search through a
PDF document and use the results in Zed's AI Assistant.
Prerequisites
This extension currently requires:
1. An OpenAI API key (to generate embeddings)
2. uv installed on your system
Note: While the current setup requires an OpenAI API key for generating embeddings, we plan to implement a self-contained alternative in future versions. Community feedback will help prioritize these improvements.
Quick Start
1. Clone the repository
git clone https://github.com/freespirit/pdfsearch-zed.git
2. Set up the Python environment for the MCP server:
cd pdfsearch-zed/pdf_rag
uv venv
uv sync
3. Install Dev Extension in Zed
4. Build the search db
```bash
cd /path/to/pdfsearch-zed/pdf_rag
echo "OPENAI_API_KEY=sk-..." > src/pdf_rag/.env
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