# agente-mcp-streamlit-ecommerce

> agente-mcp-streamlit-ecommerce — emersonelio-agente-mcp-streamlit-ecommerce. Use this tool when you need to query an e-commerce dataset using natural language, and retrieve specific data from a SQLite database. It solves problems related to data retrieval and analysis by executing parameterized SQL queries, and provides interfaces through Streamlit or Claude Desktop. The tool is ideal for use cases where users want to access e-commerce data without needing to write complex SQL queries.

Canonical page: https://skillsregistry.net/skills/emersonelio-agente-mcp-streamlit-ecommerce  
JSON: https://api.skillsregistry.net/v1/skills/emersonelio-agente-mcp-streamlit-ecommerce

## Description

Enables natural-language querying of an e-commerce dataset by providing a LangChain agent that uses tools to execute parameterized SQL queries on a SQLite database, with short-term memory and Streamlit or Claude Desktop interfaces.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/z8focz32db)
- **Repository:** <https://github.com/emersonelio/agente-mcp-streamlit-ecommerce>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "emersonelio-agente-mcp-streamlit-ecommerce"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/emersonelio-agente-mcp-streamlit-ecommerce` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/emersonelio-agente-mcp-streamlit-ecommerce/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt