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MCP server CX Codex

IterableData — Claude Code MCP server: read and convert data

Give an agent tools to read and convert files across many data formats, one record at a time. Handy when nested structures need to stay intact.

Install into Claude Code · Platform CLI All methods and platforms ↓
claude mcp add iterabledata -- uvx iterabledata
Open on GitHub

What IterableData does

IterableData lets an agent inspect and transform data files in formats such as CSV, JSON, Parquet, and XML. It processes records through an iterator-based interface and keeps nested structures intact. Ask it to identify a file’s format or convert a group of files.

In Claude Code, connect the server with claude mcp add iterabledata -- uvx iterabledata. The project description also gives iterable-mcp as the launch command after installing iterabledata[mcp]. Format detection can use a filename or file contents, and compressed files are supported. Malformed input raises a typed error by default, so it won’t be silently treated as an empty dataset.

What it helps with

  • read records from a file with an unknown format
  • convert CSV records to JSONL
  • batch-convert files in a directory
  • inspect nested fields in a data file

Example prompts for the agent

  • Identify the format of data.bin and read its records.
  • Convert the CSV files in this folder to JSONL.
  • Show the nested fields in events.json.

How to install IterableData

Platform CLI

claude mcp add iterabledata -- uvx iterabledata

uvx runs the command named after the package; if the README names another one, use uvx --from iterabledata <command>

Step by step, with commands for each platform: How to add an MCP server to Claude Code, Codex, Cursor, VS Code, Gemini CLI and more

Questions about IterableData

How do I install IterableData in Claude Code?

Run claude mcp add iterabledata -- uvx iterabledata.

What does IterableData do?

It gives an agent tools to read, inspect, and convert files across data formats while processing records one at a time.

Does IterableData preserve nested data?

Yes. Nested structures are handled as Python dictionaries rather than flattened into tables.

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