Prototype · Preview: every server in the official registry, synced every 30 minutes. Reviews and accounts come in a later step.
PopNx MCPMCP servers for people who use AI · explained in plain words
Beginner mode Off
ColoursSystemLightDark
LanguageไทยEnglish中文日本語한국어EspañolDeutsch
☰ MenuSettings
Beginner mode Off
ColoursSystemLightDark
LanguageไทยEnglish中文日本語한국어EspañolDeutsch

IterableData

by datenoioversion 1.1.0i★ –iRuns on your computer
Registry nameio.github.datenoio/iterabledata

Install

Overview

Description from the maker (original English)

Streaming read, convert, and inspect 100+ formats. Install iterabledata[mcp] and run iterable-mcp.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "iterabledata": {
      "command": "uvx",
      "args": [
        "iterabledata"
      ]
    }
  }
}

Run this in your terminal

claude mcp add iterabledata -- uvx iterabledata

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "iterabledata": {
      "command": "uvx",
      "args": [
        "iterabledata"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "iterabledata": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "iterabledata"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account datenoio, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32484 servers in this category
  • Published to the registry more recently than 80% of the other 32484 servers in this category
  • Basic checks equal to or better than 100% of the other 32484 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is IterableData safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.1.0) reached the registry 8 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Recta

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
Install

Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday
Install

Recta

by RectaBuild

Cheaper cross-chain stablecoin routes for AI agents; 5 % of the verified saving, nothing if none.

Computer or cloudUpdated today
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Iterable Data

Iterable Data is a Python library for reading and writing data files row by row in a consistent, iterator-based interface. It provides a unified API for working with various data formats (CSV, JSON, Parquet, XML, etc.) similar to csv.DictReader but supporting many more formats.

This library simplifies data processing and conversion between formats while preserving complex nested data structures (unlike pandas DataFrames which require flattening).

Features

  • Unified API: Single interface for reading/writing multiple data formats
  • Automatic Format Detection: Detects file type and compression from filename or content (magic numbers and heuristics)
  • Format Capability Reporting: Programmatically query format capabilities (read/write/bulk/totals/streaming/tables)
  • Support for Compression: Works seamlessly with compressed files
  • Preserves Nested Data: Handles complex nested structures as Python dictionaries
  • DuckDB Integration: Optional DuckDB engine for high-performance queries with pushdown optimizations
  • Pipeline Processing: Built-in pipeline support for data transformation
  • Encoding Detection: Automatic encoding and delimiter detection for text files
  • Bulk Operations: Efficient batch reading and writing
  • Native Batch Conversion: Opt-in columnar-to-columnar transfers with projection, row-range, and batch-size selection
  • Bounded Columnar I/O: Shared row/bulk cursors and configurable Parquet row groups keep large reads and writes bounded
  • Codec Performance Profiles: Choose fast, balanced, or max compression settings with effective-setting diagnostics
  • Table Listing: Discover available tables, sheets, and datasets in multi-table formats
  • Context Manager Support: Use with statements for automatic resource cleanup
  • DataFrame Bridges: Convert iterable data to Pandas, Polars, and Dask DataFrames with one-liner methods
  • Cloud Storage Support: Direct access to S3, GCS, and Azure Blob Storage via URI schemes
  • Database Engine Support: Read-only access to SQL and NoSQL databases (PostgreSQL, ClickHouse, MySQL, MongoDB, Elasticsearch, etc.) as iterable data sources
  • Atomic Writes: Production-safe file writing with temporary files and atomic renames
  • Bulk File Conversion: Convert multiple files at once using glob patterns or directories
  • Progress Tracking and Metrics: Built-in progress bars, callbacks, and structured metrics objects
  • Error Handling Controls: Configurable error policies and structured error logging; malformed input raises typed errors by default instead of reading as empty datasets
  • Security Hardening: XXE-safe XML parsing, AST-whitelisted filter expressions, and explicit pickle trust acknowledgement
  • Performance Regression Gate: CI-enforced baselines for representative read/convert workloads
  • Container Formats: Stream records from TAR archives without extracting members to disk
  • Type Hints and Type Safety: Complete type annotations with typed helper functions for dataclasses and Pydantic models
  • Lakehouse Tables: Read and write Delta Lake, Iceberg, and DuckLake; read Hudi; experimental Apache Paimon tables plus Row/Mosaic file formats

Supported File Types

Core Formats
  • JSON - Standard JSON files
  • JSONL/NDJSON - JSON Lines format (one JSON object per line)
  • JSON-LD - JSON for Linking Data (RDF format)
  • CSV/TSV - Comma and tab-separated values
  • Annotated CSV - CSV with type annotations and metadata
  • CSVW - CSV on the Web (with metadata)
  • PSV/SSV - Pipe and semicolon-separated values
  • LTSV - Labeled Tab-Separated Values
  • FWF - Fixed Width Format
  • XML - XML files with configurable tag parsing
  • ZIP XML - XML files within ZIP archives
  • HTML - HTML files with table extraction
Binary Formats
  • BSON - Binary JSON format
  • MessagePack - Efficient binary serialization
  • CBOR - Concise Binary Object Representation
  • UBJSON - Universal Binary JSON
  • SMILE - Binary JSON variant
  • Bencode - BitTorrent encoding format
  • Avro - Apache Avro binary format (read & write)
  • Pickle - Python pickle format (untrusted input is unsafe; pass trust=True to acknowledge)
Columnar & Analytics Formats
  • Parquet - Apache Parquet columnar format
  • ORC - Optimized Row Columnar format
  • Arrow/Feather - Apache Arrow columnar format
  • GeoParquet - GeoParquet metadata-aware Parquet profile with geometry/CRS preservation
  • Lance - Modern columnar format optimized for ML and vector search
  • Vortex - Modern columnar format with fast random access
  • Paimon Row - Apache Paimon row format for O(1) row-number access
  • Paimon Mosaic - Apache Paimon columnar-bucket format for wide tables
  • Paimon - Apache Paimon warehouse/catalog tables
  • Delta Lake - Delta Lake format (read & write)
  • Iceberg - Apache Iceberg format (read & write)
  • DuckLake - DuckLake lakehouse tables (read & write)
  • Hudi - Apache Hudi format (read; writes deferred)
Database Formats
  • SQLite - SQLite database files
  • DBF - dBase/FoxPro database files
  • MySQL Dump - MySQL dump files
  • PostgreSQL Copy - PostgreSQL COPY format
  • DuckDB - DuckDB database files
Statistical Formats
  • SAS - SAS data files
  • Stata - Stata data files
  • SPSS - SPSS data files
  • R Data - R RDS and RData files
  • fst - R fst columnar on-disk frames (fst extra; experimental)
  • PX - PC-Axis format
  • ARFF - Attribute-Relation File Format (Weka format)
  • LIBSVM - Sparse labeled feature vectors (read & write)
  • NumPy - .npy / .npz array rows (read & write; npy extra)
Scientific Formats
  • NetCDF - Network Common Data Form for scientific data
  • CDF - NASA Common Data Format (space science)
  • HDF5 - Hierarchical Data Format
  • Zarr - Chunked array stores (zarr extra; experimental)
  • XYZ - Molecular/point coordinate tables
  • CIF - Crystallographic Information File (atom_site loops; experimental)
  • PDB - Protein Data Bank ATOM/HETATM records
  • MATLAB MAT - MATLAB .mat variables (mat extra; experimental)
  • SEG-Y - Seismic traces (geophysical extra; experimental)
  • GRIB2 - Meteorological messages (geophysical extra; experimental)
  • miniSEED - Seismological waveform windows (geophysical extra; experimental)
Geospatial Formats
  • GeoJSON - Geographic JSON format
  • GeoJSON Text Sequence - RFC 8142 line-delimited GeoJSON Features (.geojsonl, .geojsons); streaming-friendly
  • GeoPackage - OGC GeoPackage format
  • GML - Geography Markup Language
  • KML - Keyhole Markup Language
  • KMZ - KML Zipped (ZIP archive containing KML)
  • GPX - GPS Exchange Format (waypoints, routes, tracks)
  • Shapefile - ESRI Shapefile format
  • File Geodatabase - ESRI FileGDB layers via Fiona (geospatial extra; experimental)
  • MapInfo MIF - MapInfo Interchange Format (geospatial extra; experimental)
  • Esri ASCII Grid - Raster grids as cell or row records (.asc)
  • ArcInfo E00 - Interchange exports (experimental subset)
  • LAS - LiDAR point clouds (lidar extra; experimental)
  • BAG - Bathymetric Attributed Grid (hdf5 extra; experimental)
  • CZML - Cesium CZML document packets
  • FlatGeobuf - Streaming geospatial features with optional spatial-index filtering
  • MVT/PBF - Mapbox Vector Tiles
  • TopoJSON - Topology-preserving GeoJSON extension
RDF & Semantic Formats
  • JSON-LD - JSON for Linking Data
  • RDF/XML - RDF in XML format
  • Turtle - Terse RDF Triple Language
  • N-Triples - Line-based RDF format
  • N-Quads - N-Triples with context
  • TriG - RDF Triple Graph format
  • N3 - Notation3 RDF format
  • TriX - XML Triple RDF format
  • HDT - Header-Dictionary-Triples compact RDF (rdf extra; experimental)
Feed Formats
  • Atom - Atom Syndication Format
  • RSS - Rich Site Summary feed format
Network Formats
  • PCAP - Packet Capture format
  • PCAPNG - PCAP Next Generation format
Log & Event Formats
  • Apache Log - Apache access/error logs
  • CEF - Common Event Format
  • GELF - Graylog Extended Log Format
  • WARC - Web ARChive format
  • CDX - Web archive index format
  • ILP - InfluxDB Line Protocol
  • HTML - HTML files with table extraction
Email Formats
  • EML - Email message format
  • MBOX - Mailbox format
  • MHTML - MIME HTML format
Configuration Formats
  • INI - INI configuration files
  • TOML - Tom's Obvious Minimal Language
  • YAML - YAML Ain't Markup Language
  • HOCON - Human-Optimized Config Object Notation
  • EDN - Extensible Data Notation
Office Formats
  • XLS/XLSX - Microsoft Excel files
  • XLSB - Excel Binary format
  • ODS - OpenDocument Spreadsheet
  • Microsoft Access - Access .mdb / .accdb tables (access extra; experimental)
  • Lotus 1-2-3 - Legacy WK1 / .123 spreadsheets (experimental)
Business & Exchange Formats
  • EDI - X12 / EDIFACT segment streams (experimental)
  • IATI - Aid-transparency activity XML (xml extra; experimental)
CAD Formats
  • DXF - AutoCAD Drawing Exchange Format
Graph Formats
  • GraphML - Graph Markup Language
  • GEXF - Graph Exchange XML Format
  • DOT - GraphViz DOT format
Sequence & Alignment Formats
  • FASTA - Sequence format (protein/nucleotide)
  • FASTQ - Sequence with quality format
  • SAM - Sequence Alignment/Map (text)
  • BAM - Binary SAM format
  • Genomic VCF/BCF - Variant Call Format for genomic data (distinct from vCard .vcf; requires bio extra)
  • CRAM - Reference-compressed sequence alignments (requires alignment extra and an explicit reference when needed)
  • BED - BED3–BED12 genomic intervals
  • GFF3/GTF - Genomic feature annotations with coordinate and attribute preservation
Streaming & Big Data Formats
  • Kafka - Apache Kafka format
  • Pulsar - Apache Pulsar format
  • Flink - Apache Flink format
  • Beam - Apache Beam format
  • RecordIO - RecordIO format
  • SequenceFile - Hadoop SequenceFile
  • TFRecord - TensorFlow Record format
  • WebDataset - TAR shards grouped into ML sample dicts (format="webdataset"; experimental)
Protocol & Serialization Formats
  • Protocol Buffers - Google Protocol Buffers
  • Cap'n Proto - Cap'n Proto serialization
  • FlatBuffers - FlatBuffers serialization
  • FlexBuffers - FlexBuffers format
  • Thrift - Apache Thrift format
  • ASN.1 - ASN.1 encoding format
  • Ion - Amazon Ion format
  • OTLP JSON/Protobuf - OpenTelemetry traces, logs, and metrics export profiles (requires otlp extra)
Other Formats
  • TAR - Multi-file archive container (read-only; streams members without extracting to disk)
  • vCard (VCF) - Electronic business cards (RFC 6350); not genomic Variant Call Format
  • iCal - iCalendar format
  • LDIF - LDAP Data Interchange Format
  • TXT - Plain text files

See the formats documentation (or docs/docs/formats/ in this repo) for per-format parameters, record shapes, and extras.

Supported Compression Codecs

  • GZip (.gz)
  • BZip2 (.bz2)
  • LZMA (.xz, .lzma)
  • LZ4 (.lz4)
  • ZIP (.zip)
  • Brotli (.br)
  • ZStandard (.zst, .zstd)
  • Snappy (.snappy, .sz) — streaming decompression for framed files
  • LZO (.lzo, .lzop) — streaming decompression with legacy blob fallback
  • 7z (.7z; requires py7zr via iterabledata[compression])

Requirements

Python 3.10+

Installation

pip install iterabledata

The PyPI package is iterabledata. Import iterable:

from i

Only the beginning is shown; read the rest in the repo

Ask PopNx