io.github.thesinbin12-jpg/getqueryly · v1.0.0 · data-and-databases
GetQueryly — AI Data Analyst is healthy: it completed an MCP handshake in 741 ms and exposes 22 tools.
Upload spreadsheets, get plain-English analysis with real computed charts and quality scores.
Endpoint: https://getqueryly.com/mcp/mcp (streamable-http)
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| Users (last 30 days) | 0 |
| Handshake | Healthy |
| Auth needed | None |
| Tool count | 22 |
| Latency | 741 ms |
| Last checked (UTC) | 2026-10-16T17:05:37.638Z |
| Checked (UTC) | Status | Latency | Error |
|---|---|---|---|
| 2026-10-16T17:05:37.638Z | Healthy | 741 | |
| 2026-10-15T11:05:12.363Z | Healthy | 1293 |
ai_chat | Chat with getqueryly AI. Ask questions, generate content, search the web. Costs 1 Make. |
ds_upload | Upload a data file for AI analysis. Supports CSV, Excel, JSON, PDF, images, SPSS, Parquet. Returns session_id. Free. |
ds_query | Ask a question about uploaded data. AI writes and runs Python code. Returns analysis with charts. Costs 1 Make. |
analyze_file | ONE-CALL deep analysis (v2): upload a file and get quality score, top insights, a summary and the headline chart — no session juggling. Without a question: full analysis (2 Makes). With a question: answers just that question (1 Make). Returns structured JSON. |
ds_health_check | Run a data health check. Detects missing values, outliers, type issues, duplicates. Costs 2 Makes. |
ds_insights | Get automatic insights from data: patterns, anomalies, trends, correlations. Costs 3 Makes. |
ds_swarm | Run analyst swarm: multiple AI personas analyze your data independently, then synthesize consensus. Depth: quick (5 Makes) or full (8 Makes). |
ds_report | Generate a PDF report from data analysis. Includes charts, stats, insights. Costs 3 Makes. |
smart_test | AI picks the right statistical test for your data and runs it. Costs 1 Make. |
chart | Generate a chart from data. Ask for any chart type: bar, line, scatter, heatmap, box plot, treemap, etc. Costs 2 Makes. |
generate_diagram | Generate a diagram from description. Types: flowchart, org_chart, process, mindmap, tree. Palettes: blue, green, purple, dark, warm. Costs 1 Make. |
generate_org_chart | Generate an org chart. names_json: JSON array of [name, role, parent_name_or_null]. Example: [["CEO John", "CEO", null], ["VP Sarah", "VP Engineering", "CEO John"]]. Costs 2 Makes. |
create_infographic | Create a professional infographic. stats_json/bars_json/progress_json: JSON arrays. Themes: corporate, vibrant, clean, nature, sunset. Costs 1 Make. |
create_comparison | Create a side-by-side comparison infographic. Costs 1 Make. |
kaggle_search | Search 200K+ Kaggle datasets by keyword. Returns dataset refs, titles, license info, download counts. Free. |
kaggle_load | Download a Kaggle dataset and create an analysis session. Returns session_id for queries. Free. |
kaggle_analyze | Search Kaggle, download dataset, and analyze it in one step. Costs 2 Makes for the query. |
get_usage | Check your getqueryly Makes balance and usage. Free. |
get_costs | Get the Makes cost table for all operations. Free. |
ds_graph | Build or query a knowledge graph for an uploaded dataset (GraphRAG). action='build' turns the data into a graph and returns a summary. action='query' answers a question over the graph (e.g. 'which products share the most suppliers?'). Costs 1 Make. |
ds_elasticity | Pricing sensitivity: if the dataset has discount + margin columns, compute per-segment margin sensitivity to discount (slope, R-squared, confidence, recommendation). Costs 1 Make. |
ds_dashboard | Auto-generate a Power BI-grade executive dashboard (KPIs, charts, pricing elasticity, impact/effort matrix, takeaways) from the uploaded dataset. Costs 2 Makes. |