$ loading_
Load datasets, compute statistics, and create charts for data exploration.
This MCP tool is described as a local data analysis and visualization utility, with no required secrets and no declared remote egress endpoint, and no clear high-risk red flags are evident. The main considerations are its local code-execution capability, access to user data files, and a supply-chain profile that is open-source and auditable but weakly validated by community adoption and maintenance signals.
The materials explicitly state that no keys or environment variables are required, and no API tokens, account credentials, or other sensitive authentication material are requested, so credential exposure and abuse risk appears low.
No remote host is declared; the mention of SSE/HTTP appears to describe the service interface rather than a specific outbound destination. Based on the provided materials, there is no factual indication that user data is sent to third-party services.
The system checks mark this tool as executes-code, indicating it can run code or processing logic on the local machine. This is a standard capability for MCP/data-analysis tools, but it still represents a local execution surface that warrants caution.
The description says it can load CSV/Excel/JSON files and explore datasets, which implies access to user-selected data files and possibly creation of chart/output files. The materials do not show data permissions clearly exceeding its stated purpose, but it does interact with local data and should be scoped minimally.
The tool is open source under the MIT License, which is a meaningful risk-reducing factor because the code is auditable; however, it comes from a third-party registry, has 0 stars, and its maintenance status is unknown, so independent trust and upkeep signals are weak and supply-chain caution is appropriate.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "data-analysis-mcp" yet — see the docs or source repo.
Please load this sales.csv, calculate sales by region, average order value, and monthly trends, then generate a bar chart and line chart and summarize the key findings in English.
Returns sales metrics, two charts, and a brief summary of regional performance and trends.
Read survey.xlsx, provide frequency distributions for each question, missing-value analysis, and basic descriptive statistics, then identify the three most notable findings.
Provides survey distributions, a data-quality overview, and three key insights.
Load metrics.json, analyze changes in DAU, retention, and conversion rate, identify anomalous time periods, and visualize the suspicious ranges with charts.
Returns metric trends, explanations of anomalous periods, and supporting visual charts.
Explore CSV datasets with summaries, cleaning, correlations, and statistical tests.
Run statistical analysis, probability calculations, and data processing through natural language.
Explore, analyze, and filter CSV data with schema and statistics tools.
Analyze local CSV or Parquet datasets and generate insights without full uploads.
Import spreadsheets, run queries, and get instant data insights with AI.
Quickly compute data metrics and descriptive statistics with clear analytical outputs.