{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_8j4422eke274","handle":"iflow-mcp-pawankumar94-sql-mcp-server","url":"https://wellknown.network/agents/iflow-mcp-pawankumar94-sql-mcp-server","links":{"self":"https://wellknown.network/agents/iflow-mcp-pawankumar94-sql-mcp-server/record.json","html":"https://wellknown.network/agents/iflow-mcp-pawankumar94-sql-mcp-server","markdown":"https://wellknown.network/agents/iflow-mcp-pawankumar94-sql-mcp-server/record.md","api":"https://wellknown.network/api/v1/agents/iflow-mcp-pawankumar94-sql-mcp-server","status":"https://wellknown.network/api/v1/agents/iflow-mcp-pawankumar94-sql-mcp-server/status","claim":"https://wellknown.network/agents/iflow-mcp-pawankumar94-sql-mcp-server/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/iflow-mcp-pawankumar94-sql-mcp-server/claim.json","badge":"https://wellknown.network/agents/iflow-mcp-pawankumar94-sql-mcp-server/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/iflow-mcp-pawankumar94-sql-mcp-server/history","tools":"https://wellknown.network/api/v1/agents/iflow-mcp-pawankumar94-sql-mcp-server/tools"},"ard":{"identifier":"urn:air::server:iflow-mcp-pawankumar94-sql-mcp-server","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"iflow-mcp-pawankumar94-sql-mcp-server","summary":"AI-Powered SQL Assistant for BigQuery using MCP","description":"# SQLGenius - AI-Powered SQL Assistant\n\n[![MCP Reviewed](https://img.shields.io/badge/MCP%20Reviewed-✓-blue.svg)](https://mcpreview.com/mcp-servers/pawankumar94/sql_mcp_server)\n\nSQLGenius is an intelligent SQL assistant that helps you query your BigQuery database using natural language. Built with MCP (Model Context Protocol), Vertex AI's Gemini Pro, and Streamlit.\n\n## 🌟 Features\n\n- Natural language to SQL conversion using Gemini Pro\n- Interactive Streamlit UI with multiple tabs\n- Real-time query execution and visualization\n- Database schema explorer\n- Query history tracking\n- Safe query validation\n- BigQuery integration\n- MCP-based architecture\n\n## 🎥 Demo\n\nWatch SQLGenius in action! Here's a quick demo of how to use the application:\n\n![SQLGenius Demo](demo.gif)\n\nIn this demo, you can see:\n1. Natural language query conversion to SQL\n2. Interactive data visualization\n3. Schema exploration\n4. Query history tracking\n\n## 🚀 Installation\n\n1. Clone the repository and navigate to the project directory:\n```bash\ncd sql_mcp_server\n```\n\n2. Install dependencies:\n```bash\npip install -r requirements.txt\n```\n\n3. Copy the `.env.example` file to `.env` and fill in your configuration:\n```bash\ncp .env.example .env\n```\n\n4. Set up your environment variables in `.env`:\n```\nPROJECT_ID=your-project-id\nDATASET_ID=your-dataset-id\nGOOGLE_APPLICATION_CREDENTIALS=path/to/your/service-account.json\nVERTEX_AI_LOCATION=us-central1\n```\n\n## 🎮 Usage\n\n1. Start the application:\n```bash\nstreamlit run streamlit_app.py\n```\n\n2. The MCP server will start automatically when the Streamlit app launches\n\n3. Use the tabs to:\n   - Ask natural language questions about your data\n   - Write SQL queries directly\n   - Explore your database schema\n\n## 📊 Interface Tabs\n\n### 💬 Natural Language Query\nAsk questions in plain English and get SQL results:\n- \"Show me the top 5 customers by revenue\"\n- \"What products have the highest sales in January?\"\n- \"How many orders were placed last month?\"\n\n### 📊 SQL Query\nWrite and …","publisher":null,"homepage":null,"repository":null,"version":"0.1.0","license":null,"protocols":["mcp"],"tags":["mcp"],"pricing":null,"endpoints":[{"url":"pypi:iflow-mcp-pawankumar94-sql-mcp-server","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":"data.database","name":"Databases","confidence":1,"provenance":"derived"},{"slug":"commerce.ecommerce","name":"E-commerce Operations","confidence":0.802,"provenance":"derived"}],"categories":["commerce","data"],"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-pawankumar94-sql-mcp-server","registry":"pypi","observedAt":"2026-11-09T10:23:19.005Z","publishedAt":"2026-02-11T14:15:31.671927Z","latestVersion":"0.1.0"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"iflow-mcp-pawankumar94-sql-mcp-server","url":"https://pypi.org/project/iflow-mcp-pawankumar94-sql-mcp-server/","firstSeenAt":"2026-09-09T20:24:56.193Z","fetchedAt":"2026-11-09T10:21:37.540Z","normalizedAt":"2026-11-09T10:21:37.540Z"}]},"firstSeenAt":"2026-09-09T20:24:56.193Z","updatedAt":"2026-11-09T10:23:19.005Z"}