Data Science Tools MCP servers & tools

Tools and templates to create validated and maintainable data charts and dashboards.

An MCP server to convert almost any file or web content into Markdown

Automated time series forecasting with model search, anomaly detection, and event risk analysis

Model Context Protocol (MCP) Server for Jupyter.

Decision intelligence MCP server with 19 algorithms (bandits, Monte Carlo, constraint optimization, forecasting, anomaly detection, risk analysis, graph algorithms), 28 MCP tools. Install via npx -y @oraclaw/mcp-server.

MCP server for the Dingo: a comprehensive data quality evaluation tool. Server Enables interaction with Dingo's rule-based and LLM-based evaluation capabilities and rules&prompts listing.

Enables autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort.

Calculator, units, statistics for AI agents

Sort up to 1,000 texts into your own labels with a calibrated confidence per answer. No API key.

Connect RStudio to AI assistants for interactive R coding and data analysis.

Let LLM help you achieve your regression analysis with Stata

Real-time LLM/VLM model comparison with benchmarks, pricing, and personalized recommendations from 5 data sources. No API key required.

connects Jupyter Notebook to Claude AI, allowing Claude to directly interact with and control Jupyter Notebooks.

Predict anything with Chronulus AI forecasting and prediction agents.

Official MCP server enabling seamless orchestration of hyperparameter search and other optimization tasks with Optuna.

Link multiple data sources (SQL, CSV, Parquet, etc.) and ask AI to analyze the data for insights and visualizations.

Statistical analysis, forecasting, and ML for business data (Shopify, Stripe, WooCommerce, eBay, GA4, Search Console). Upload a CSV or connect live data sources — ask a question in Claude or Cursor, get an interactive HTML report.

Wolfram Alpha MCP — computational, factual, and quantitative queries

Connects to Kaggle, ability to download and analyze datasets.

通过 pystata 驱动真实 Stata 的 MCP 服务器：数据加载/清洗/建模/诊断/图形导出，75 个工具覆盖完整计量工作流。

Create, manage, and automate Label Studio projects, tasks, and predictions for data labeling workflows.

Model Context Protocol for R: enables AI agents to participate in interactive live R sessions.

Control FiftyOne computer vision datasets through AI assistants using 80+ operators.

Tools for creating and interacting with GrowthBook feature flags and experiments.

The ultimate math engine unifying SymPy, NumPy & Matplotlib in one powerful server. Perfect for developers & researchers needing symbolic algebra, numerical computing, and data visualization.

The first NetworkX integration for Model Context Protocol, enabling graph analysis and visualization directly in AI conversations. Supports 13 operations including centrality algorithms, community detection, PageRank, and graph visualization.

50+ pandas-powered tools for data loading, cleaning, visualization, and ML workflows

Airtight math for agents: 3.7M-theorem search, PSLQ constant ID, OEIS, real Lean kernel checks, applicability checklists. No LLM inside, no API key.

Qualify dataset columns and process them against a target with AutoCarver, fully on your machine.

Superhuman exploratory data analysis that finds the feature interactions and subgroup effects that LLMs and manual exploration miss — with p-values, effect sizes, and literature citations. Data goes in, validated insights come out. Free for public data.

Educational MCP server for math operations, statistics, visualization, and persistent workspaces. Built with FastMCP 2.0.

Discover, validate, preview, tune, and export AlbumentationsX augmentation pipelines through MCP.

LLM quantization via tool call. Convert models to GGUF, GPTQ, and AWQ formats. Recommend optimal quant settings, evaluate quality, and push to Hugging Face Hub.

Physics-based anomaly detection via MCP. Uses Klein-Gordon wave equations on GPU to detect anomalies with high precision (avg 0.90). 9 tools: scan, fingerprint, compare, token risk, wallet profiling, volume check, price manipulation detection.

MCP server for the Kaggle API: competitions, datasets, kernels, and models.

Create, read, validate, and save Stella system dynamics models (.stmx files in XMILE format) for scientific simulation and modeling.

GPU-accelerated MCP server: symbolic algebra, numerical computing, FFT, optimization, linear algebra

This MCP server enables users to perform scientific computations regarding linear algebra and vect…

Data compression MCP server. 7 tools for gzip, brotli, deflate, and TurboQuant quantization. Auto-selects best algorithm. 60x compression on docs. Zero dependencies.

Profiles tabular data files (CSV, TSV, Parquet, Excel, JSON) for LLM agents: one-call dataset overview, per-column statistics, a data-quality audit (missing values, duplicates, mixed types, outliers), and memory-saving dtype suggestions. Pure Python (pandas); files are read locally and nothing leaves your machine. pip install data-profiler-mcp.

Structural observability for AI conversations. Detects loops, stuck states, breakthroughs, and convergence across 17 channels without analyzing content.

Self-hosted MCP server for time-series forecasting and tabular ML via foundation models.

Unit conversion and dimensional analysis backed by the bundled GNU units database (3000+ units, compound expressions, reduction to SI base units). Offline and deterministic. uvx mcp-gnu-units.

Deterministic batch tools so LLM agents stop next-token-guessing dates and math. Rich now() snapshot (18 fields), calendar(ops) batch dispatcher (diff/until/since/add/weekday/businessdays, natural-language parsing), calc(expressions) Python eval with math+stats pre-loaded, and Pint-based unit conversion. One wiring for dates + math + units. Listed in the official MCP Server Registry. uvx gnomon-mcp.

Compares approximate filter data structures (Bloom, Counting Bloom, Cuckoo, SuRF) via MCP

Profile local CSV, Parquet, JSON and Excel files into a compact data-quality summary.

Agent-operable ML experiment contract (cq.yaml + JSON contracts) with a built-in MCP server exposing 14 tools (resolve/inspect/run/validate/describe/compare/lineage) for running, validating, and tracing experiments across any framework (PyTorch / HF Trainer / Lightning / sklearn / XGBoost). Apache-2.0.

Verified statistical inference for AI agents: t-tests, effect sizes, power, and corrections.

Train, explain, optimise and deploy transparent glass-box ML models via workflow tools.

Real Monte Carlo simulation of a compound event/conditional probability. Paid via x402.

Causal DAG analysis: backdoor paths, adjustment sets, bias simulation. Validated against dagitty.

An MCP server that exposes NumPy functionality

Safety-first Kaggle MCP — confirm-gated destructive ops, submission budget, injection-fenced.

LLM-native optimization solver: LP, MIP, portfolio & scheduling via HiGHS/OR-Tools.

Roboflow computer vision for AI agents: datasets, annotation, versioning, workflows, inference.

An MCP server that provides text preprocessing, NLP components, and document analysis

Is this number real, or is it noise? Peek-safe A/B tests, change detection, honest forecasts.

Monte Carlo decision-intelligence over MCP: simulate, optimize, and decide under uncertainty.

Generate random values and probability distribution samples.

MCP server for the Codabench REST API — drives a full ML-benchmark participant workflow.