{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_63qyysbsp6jx","handle":"iflow-mcp-mcp-server-ds","url":"https://wellknown.network/agents/iflow-mcp-mcp-server-ds","links":{"self":"https://wellknown.network/agents/iflow-mcp-mcp-server-ds/record.json","html":"https://wellknown.network/agents/iflow-mcp-mcp-server-ds","markdown":"https://wellknown.network/agents/iflow-mcp-mcp-server-ds/record.md","api":"https://wellknown.network/api/v1/agents/iflow-mcp-mcp-server-ds","status":"https://wellknown.network/api/v1/agents/iflow-mcp-mcp-server-ds/status","claim":"https://wellknown.network/agents/iflow-mcp-mcp-server-ds/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/iflow-mcp-mcp-server-ds/claim.json","badge":"https://wellknown.network/agents/iflow-mcp-mcp-server-ds/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/iflow-mcp-mcp-server-ds/history","tools":"https://wellknown.network/api/v1/agents/iflow-mcp-mcp-server-ds/tools"},"ard":{"identifier":"urn:air::server:iflow-mcp-mcp-server-ds","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"iflow-mcp-mcp-server-ds","summary":"A MCP server project","description":"# MCP Server for Data Exploration\n\nMCP Server is a versatile tool designed for interactive data exploration.\n\nYour personal Data Scientist assistant, turning complex datasets into clear, actionable insights.\n\n<a href=\"https://glama.ai/mcp/servers/hwm8j9c422\"><img width=\"380\" height=\"200\" src=\"https://glama.ai/mcp/servers/hwm8j9c422/badge\" alt=\"mcp-server-data-exploration MCP server\" /></a>\n\n## 🚀 Try it Out\n\n1. **Download Claude Desktop**\n   - Get it [here](https://claude.ai/download)\n\n2. **Install and Set Up**\n   - On macOS, run the following command in your terminal:\n   ```bash\n   python setup.py\n   ```\n\n3. **Load Templates and Tools**\n   - Once the server is running, wait for the prompt template and tools to load in Claude Desktop.\n\n4. **Start Exploring**\n   - Select the explore-data prompt template from MCP\n   - Begin your conversation by providing the required inputs:\n     - `csv_path`: Local path to the CSV file\n     - `topic`: The topic of exploration (e.g., \"Weather patterns in New York\" or \"Housing prices in California\")\n\n## Examples\n\nThese are examples of how you can use MCP Server to explore data without any human intervention.\n\n### Case 1: California Real Estate Listing Prices\n- Kaggle Dataset: [USA Real Estate Dataset](https://www.kaggle.com/datasets/ahmedshahriarsakib/usa-real-estate-dataset)\n- Size: 2,226,382 entries (178.9 MB)\n- Topic: Housing price trends in California\n\n[![Watch the video](https://img.youtube.com/vi/RQZbeuaH9Ys/hqdefault.jpg)](https://www.youtube.com/watch?v=RQZbeuaH9Ys)\n- [Data Exploration Summary](https://claude.site/artifacts/058a1593-7a14-40df-bf09-28b8c4531137)\n\n### Case 2: Weather in London\n- Kaggle Dataset: [2M+ Daily Weather History UK](https://www.kaggle.com/datasets/jakewright/2m-daily-weather-history-uk/data)\n- Size: 2,836,186 entries (169.3 MB)\n- Topic: Weather in London\n- Report: [View Report](https://claude.site/artifacts/601ea9c1-a00e-472e-9271-3efafb8edede)\n- Graphs:\n  - [London Temperature Trends](https://claude.si…","publisher":null,"homepage":null,"repository":null,"version":"0.1.6","license":null,"protocols":["mcp"],"tags":["mcp"],"pricing":null,"endpoints":[{"url":"pypi:iflow-mcp-mcp-server-ds","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","summary":"pypi","version":"pypi","description":"pypi"}},"derived":{"capabilities":[{"slug":"ai.prompting","name":"Prompt Management","confidence":0.802,"provenance":"derived"},{"slug":"dev.terminal","name":"Terminal & Shell","confidence":0.779,"provenance":"derived"}],"categories":["ai","dev"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"iflow-mcp-mcp-server-ds","registry":"pypi","observedAt":"2026-09-15T19:23:11.009Z","publishedAt":"2025-11-21T02:37:08.409542Z","latestVersion":"0.1.6"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"iflow-mcp-mcp-server-ds","url":"https://pypi.org/project/iflow-mcp-mcp-server-ds/","firstSeenAt":"2026-09-09T20:23:43.623Z","fetchedAt":"2026-09-15T19:21:18.955Z","normalizedAt":"2026-09-15T19:21:18.955Z"}]},"firstSeenAt":"2026-09-09T20:23:43.623Z","updatedAt":"2026-09-15T19:23:11.009Z"}