Parquet MCP Server
Description
# parquet_mcp_server [](https://smithery.ai/server/@DeepSpringAI/parquet_mcp_server) A powerful MCP (Model Control Protocol) server that provides tools for manipulating and analyzing Parquet files. This…
About
# parquet_mcp_server [](https://smithery.ai/server/@DeepSpringAI/parquet_mcp_server) A powerful MCP (Model Control Protocol) server that provides tools for manipulating and analyzing Parquet files. This server is designed to work with Claude…
Details
- Author
- DeepSpringAI
- Downloads
- 201
- Categories
- Search, Other, AI
Jump to
- Generate text embeddings from Parquet columns
- Extract Parquet file schema and metadata
- Convert Parquet to DuckDB databases
- Convert Parquet to PostgreSQL tables with pgvector
- Process markdown files into structured chunks
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
Parquet MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install via Smithery (npx -y @smithery/cli install @DeepSpringAI/parquet_mcp_server --client claude) or clone the repository and install with uv pip install -e .. Configure environment variables in a .env file (embedding URL, Ollama URL, embedding model, PostgreSQL credentials). Add the server to Claude Desktop configuration, then invoke tools using natural language prompts or the provided client functions.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"parquet mcp server": {
"parquet_mcp_server": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"install",
"@DeepSpringAI/parquet_mcp_server",
"--client",
"claude"
]
}
}
}
}McpServers
{
"parquet_mcp_server": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"install",
"@DeepSpringAI/parquet_mcp_server",
"--client",
"claude"
]
}
}parquet_mcp_server
A powerful MCP (Model Control Protocol) server that provides tools for manipulating and analyzing Parquet files. This server is designed to work with Claude Desktop and offers five main functionalities:
1. Text Embedding Generation: Convert text columns in Parquet files into vector embeddings using Ollama models
2. Parquet File Analysis: Extract detailed information about Parquet files including schema, row count, and file size
3. DuckDB Integration: Convert Parquet files to DuckDB databases for efficient querying and analysis
4. PostgreSQL Integration: Convert Parquet files to PostgreSQL tables with pgvector support for vector similarity search
5. Markdown Processing: Convert markdown files into chunked text with metadata, preserving document structure and links
This server is particularly useful for:
- Data scientists working with large Parquet datasets
- Applications requiring vector embeddings for text data
- Projects needing to analyze or convert Parquet files
- Workflows that benefit from DuckDB's fast querying capabilities
- Applications requiring vector similarity search with PostgreSQL and pgvector
Installation
Installing via Smithery
To install Parquet MCP Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @DeepSpringAI/parquet_mcp_server --client claude
Clone this repository
git clone ...
cd parquet_mcp_server
Create and activate virtual environment
uv venv
.venv\Scripts\activate # On Windows
source .venv/bin/activate # On macOS/Linux
Install the package
uv pip install -e .
Environment
Create a .env file with the following variables:
```bash
EMBEDDING_URL= # URL for the embedding service
OLLAMA_URL= # URL for Ollama server
EMBEDDING_MODEL=nomic-embed-text # Model to use for generating embeddings
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