Best for
- Data exploration in scientific computing and HPC environments.
- AI agents that need to quickly summarize Parquet files.
- Workflows integrated with the CLIO Kit ecosystem, where other servers provide complementary functions.
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55FMRS · C
CLIO Parquet is a specialized MCP server for reading Apache Parquet files. It provides essential tools for summarizing, row reading, column preview, and aggregation statistics. Being part of the CLIO Kit ecosystem, it supports scientific and HPC contexts. Its functionality is clear but limited; it is suitable for its targeted use of summarization and reading, but may not cover complex full data analysis needs.
CLIO Parquet is an MCP server for reading and analyzing Apache Parquet files, part of the CLIO Kit, a tooling layer of the IoWarp platform. It offers tools to get file summaries, read row slices, preview column values, and compute column statistics. The server is distributed via the Python package clio-kit and communicates over stdio. It is suitable for scientific or tabular data analysis where data is stored in Parquet format, often within HPC environments.
Tools
summarize_tool
Return Parquet schema, row count, and file size.
read_slice_tool
Read a row slice from a Parquet file with optional column projection and filtering.
get_column_preview_tool
Preview values from a specific column with pagination.
aggregate_column_tool
Compute aggregate statistics (min, max, mean, etc.) on a Parquet column.
Setup
- Ensure you have Python 3.10+ and the uv package manager installed.\n2. Install clio-kit with
uv tool install 'clio-kit==2.10.6'.\n3. Runuv tool update-shellif the executable directory is not on PATH.\n4. Verify server list:clio-kit mcp-servers.\n5. Start the server:clio-kit mcp-server parquet.
Fit and risk
Not for
- Full-fledged data analysis with complex transformations (e.g., group by aggregates), which might require dedicated tools.
- Handling extremely large files where the entire data cannot fit into memory for operations like reading all rows.
Required permissions
- Read access to Parquet files in the local file system as provided by the user.
- Perform file I/O to read file metadata and contents.
Risks and side effects
- Potential exposure of sensitive data if inputs include unexpected file paths.
- Resource-intensive operations on large files or complex queries could lead to excessive memory or CPU consumption.
Troubleshooting
- If the server is not found, verify the server name is `parquet` (not `parquet-mcp`).
- For import errors, run `uv sync --all-extras --dev` in the `clio-kit-mcp-servers/parquet` directory for local development.
- If `clio-kit` is not found, install uv and run `uv tool install 'clio-kit==2.10.6'`, then update the shell with `uv tool update-shell`.
Use cases
Quickly obtain the schema, row count, and size of a Parquet file.
Read row slices from a Parquet file for inspection with optional filtering.
Preview values from a specific column to get a first look at the data.
Compute statistical summaries, like mean or max, on a Parquet column.
Supported clients
Claude DesktopFull support
Claude CodeFull support
CursorFull support
VS CodeFull support