{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_xe62vn4ufhg8","handle":"iflow-mcp-linear-regression-mcp","url":"https://wellknown.network/agents/iflow-mcp-linear-regression-mcp","links":{"self":"https://wellknown.network/agents/iflow-mcp-linear-regression-mcp/record.json","html":"https://wellknown.network/agents/iflow-mcp-linear-regression-mcp","markdown":"https://wellknown.network/agents/iflow-mcp-linear-regression-mcp/record.md","api":"https://wellknown.network/api/v1/agents/iflow-mcp-linear-regression-mcp","status":"https://wellknown.network/api/v1/agents/iflow-mcp-linear-regression-mcp/status","claim":"https://wellknown.network/agents/iflow-mcp-linear-regression-mcp/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/iflow-mcp-linear-regression-mcp/claim.json","badge":"https://wellknown.network/agents/iflow-mcp-linear-regression-mcp/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/iflow-mcp-linear-regression-mcp/history","tools":"https://wellknown.network/api/v1/agents/iflow-mcp-linear-regression-mcp/tools"},"ard":{"identifier":"urn:air::server:iflow-mcp-linear-regression-mcp","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"iflow-mcp_linear-regression-mcp","summary":"MCP server for training Linear Regression Model","description":"[![MseeP.ai Security Assessment Badge](https://mseep.net/pr/heetvekariya-linear-regression-mcp-badge.png)](https://mseep.ai/app/heetvekariya-linear-regression-mcp)\n\n# Linear Regression MCP\n\nWelcome to **Linear Regression MCP**! This project demonstrates an end-to-end machine learning workflow using Claude and the Model Context Protocol (MCP). \n\n**Claude** can train a **Linear Regression model** entirely by itself, simply by uploading a CSV file containing the dataset. The system goes through the entire **ML model training lifecycle**, handling data preprocessing, training, and evaluation (RMSE calculation).\n\n[![Verified on MseeP](https://mseep.ai/badge.svg)](https://mseep.ai/app/faff0b8f-a4c5-42f6-88c4-b3cb210f4559)\n\n<br>\n\n## Setup and Installation\n\n### 1. Clone the Repository:\n\nFirst, clone the repository to your local machine:\n\n```bash\ngit clone https://github.com/HeetVekariya/Linear-Regression-MCP\ncd Linear-Regression-MCP\n```\n\n### 2. Install `uv`:\n\n`uv` is an extremely fast Python package and project manager, written in Rust. It is essential for managing the server and dependencies in this project.\n\n- Download and install `uv` from [here](https://docs.astral.sh/uv/#installation).\n\n### 3. Install Dependencies:\n\nOnce uv is installed, run the following command to install all necessary dependencies:\n\n```bash\nuv sync\n```\n\n### 4. Configure Claude Desktop:\n\nTo integrate the server with Claude Desktop, you will need to modify the Claude configuration file. Follow the instructions for your operating system:\n\n- For macOS or Linux:\n\n```bash\ncode ~/Library/Application\\ Support/Claude/claude_desktop_config.json\n```\n\n- For Windows:\n\n```bash\ncode $env:AppData\\Claude\\claude_desktop_config.json\n```\n\n- In the configuration file, locate the `mcpServers` section, and replace the placeholder paths with the absolute paths to your `uv` installation and the Linear Regression project directory. It should look like this:\n\n```bash\n{\n    \"mcpServers\":\n    {\n        \"linear-regression\": \n  …","publisher":null,"homepage":null,"repository":null,"version":"0.1.0","license":null,"protocols":["mcp"],"tags":["mcp"],"pricing":null,"endpoints":[{"url":"pypi:iflow-mcp_linear-regression-mcp","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":"dev.version-control","name":"Version Control","confidence":1,"provenance":"derived"},{"slug":"dev.project-management","name":"Project Management","confidence":1,"provenance":"derived"},{"slug":"dev.package-management","name":"Packages & Dependencies","confidence":0.859,"provenance":"derived"}],"categories":["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_linear-regression-mcp","registry":"pypi","observedAt":"2026-09-15T18:22:11.403Z","publishedAt":"2025-11-28T03:19:14.814140Z","latestVersion":"0.1.0"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"iflow-mcp_linear-regression-mcp","url":"https://pypi.org/project/iflow-mcp_linear-regression-mcp/","firstSeenAt":"2026-09-09T19:24:53.091Z","fetchedAt":"2026-09-15T18:21:20.781Z","normalizedAt":"2026-09-15T18:21:20.781Z"}]},"firstSeenAt":"2026-09-09T19:24:53.091Z","updatedAt":"2026-09-15T18:22:11.403Z"}