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RefineDataMCP

by Enesp4rl4k
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RefineData MCP Server

RefineData MCP is a Model Context Protocol server that gives AI agents (Claude Code, Cursor, ChatGPT) a toolbox for data preparation, anonymization, analysis, and visualization. It leans on Polars and DuckDB so the heavy tools stream data out-of-core instead of loading everything into RAM.

Tools

Analysis & Profiling

Tool

Purpose

Engine

Scales beyond RAM?

analyze_data

Row counts, schema, numeric stats

DuckDB

✅ out-of-core

profile_data

Per-column null rates, unique counts, sample values, date ranges

DuckDB

✅ out-of-core

sample_data

Preview N rows (head/tail/random/stratified)

DuckDB

✅ out-of-core

simplify_quant_data

Percentiles, skew, correlations

Polars (lazy/streaming)

◐ streamed

validate_schema

Check columns and types against an expected schema

DuckDB

✅ out-of-core

Cleaning & Transformation

Tool

Purpose

Engine

Scales beyond RAM?

process_data

Dedup + missing-value handling

Polars (lazy/streaming)

◐ streamed

convert_format

CSV ↔ Parquet ↔ JSONL with compression options

Polars (lazy/streaming)

◐ streamed

merge_datasets

Join two datasets on key columns

DuckDB

✅ out-of-core

detect_outliers

IQR or z-score outlier extraction

DuckDB

✅ out-of-core

ML / NLP

Tool

Purpose

Engine

Scales beyond RAM?

filter_toxic_data

Drop toxic rows (batched inference)

Detoxify

✗ in-memory

anonymize_data

Mask PII in text columns

Presidio NLP

✗ in-memory

Generation & Database

Tool

Purpose

Engine

Scales beyond RAM?

generate_synthetic_data

Schema-driven synthetic dataset generation

Polars

✗ in-memory

query_db

Run SQL on PostgreSQL/SQLite → file

DuckDB

✅ out-of-core

scrape_web_data

Extract the main HTML table from a URL

requests + BeautifulSoup

✗ in-memory

Session Management

Tool

Purpose

load_dataset

Load a file into the in-process cache, returns a handle

release_dataset

Free a cached dataset from memory

list_datasets

List all currently loaded dataset handles

Visualization

Tool

Purpose

Engine

Scales beyond RAM?

visualize_dataset

Heatmap/scatter/boxplot/bar → image

Matplotlib/Seaborn

✗ in-memory

◐ = the streamable parts of the plan run in chunks; the result is materialized. The PII/toxicity/scraping/viz tools load the working set into memory by design.

Related MCP server: Quack MCP

Installation

Core install (only analyze_data + query_db) is lightweight. Heavy features are optional extras, so you don't pull in PyTorch/spaCy/Matplotlib unless you need them.

python -m venv venv && . venv/Scripts/activate   # Windows
# source venv/bin/activate                       # Linux/Mac

pip install -e .                # core (DuckDB + Polars)
pip install -e ".[scraping]"    # + web scraper
pip install -e ".[viz]"         # + visualizer
pip install -e ".[pii]"         # + PII anonymizer
pip install -e ".[toxicity]"    # + toxicity filter
pip install -e ".[all]"         # everything

If you call a tool whose extra isn't installed, it returns a clear message telling you which pip install to run.

The PII tool also needs a spaCy model:

python -m spacy download en_core_web_sm

Supported Python: 3.11+ for core/[scraping]/[viz]; the [pii]/[toxicity] extras are pinned to 3.11–3.12 until spaCy/PyTorch ship newer wheels.

Configuration for MCP clients

Once published, run with zero local setup via uv — no clone, no venv:

{
  "mcpServers": {
    "RefineDataMCP": {
      "command": "uvx",
      "args": ["--from", "refinedata-mcp[all]", "refinedata-mcp"]
    }
  }
}

Drop [all] (or swap in [scraping], [viz], etc.) to install only the extras you need. uvx fetches the package into an isolated, cached environment on first run.

Running from a local checkout

{
  "mcpServers": {
    "RefineDataMCP": {
      "command": "refinedata-mcp",
      "cwd": "/absolute/path/to/refinedata-mcp"
    }
  }
}

refinedata-mcp is installed as a console script. Alternatively use "command": "python", "args": ["-m", "refinedata_mcp"].

Environment variables

Variable

Default

Effect

REFINEDATA_LOG_LEVEL

INFO

Log verbosity (logs go to stderr)

REFINEDATA_AUDIT_LOG

unset

Path to a JSONL audit log file (tool name, status, duration)

REFINEDATA_MAX_FILE_SIZE_MB

1024

Reject in-memory loads larger than this (0 = off)

REFINEDATA_WORKDIR

unset

Sandbox: restrict all file reads/writes to this dir

REFINEDATA_ENABLED_TOOLS

all

Comma-separated tool names to expose, or all

REFINEDATA_MAX_CONCURRENT

0

Max simultaneous tool calls (0 = unlimited)

REFINEDATA_HTTP_TIMEOUT

15

Web scraper request timeout (seconds)

REFINEDATA_ALLOW_PRIVATE_URLS

false

Allow scraping private/loopback IPs (SSRF override)

REFINEDATA_DB_READ_ONLY

true

Attach external databases read-only

REFINEDATA_DB_TIMEOUT

60

Best-effort DB query timeout (seconds, 0 = off)

REFINEDATA_PII_LANGUAGE

en

Presidio scan language

REFINEDATA_PII_BATCH_SIZE

256

Cells per spaCy nlp.pipe() batch in anonymize_data

REFINEDATA_DETOXIFY_MODEL

original

Detoxify model variant

Security notes

  • The web scraper blocks requests to private/loopback/link-local/metadata IPs (SSRF guard). Override only for trusted local use with REFINEDATA_ALLOW_PRIVATE_URLS=true.

  • query_db executes the SQL you pass it and attaches databases read-only by default.

  • Set REFINEDATA_WORKDIR to confine file access to a single directory.

  • Set REFINEDATA_ENABLED_TOOLS to expose only a subset of tools in multi-tenant setups.

  • This server is built for a single trusted user (your agent). Do not expose it to untrusted input without adding allow-lists.

Testing

pip install -e ".[dev]"
python -m pytest

Tests for optional features importorskip their dependencies, so the suite runs (skipping what isn't installed) at any install level. See ROADMAP.md for what's done and what's next.

This server cannot be installed

A
license - permissive license
-
quality - not tested
B
maintenance

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Maintenance

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–Response time
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