Loading…
Routes natural-language shopping queries to merchant storefronts, returns normalized results.
BizNetAI is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 67/100. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding BizNetAI to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
mcp add io.github.biznetai/biznetai-mcp https://biznetaimcp.consumergenie.net/mcpReview the upstream source before running this command.
{
"_meta": {
"io.modelcontextprotocol.registry/official": {
"status": "active",
"isLatest": true,
"updatedAt": "2026-07-13T22:59:21.044479Z",
"publishedAt": "2026-07-13T22:59:21.044479Z",
"statusChangedAt": "2026-07-13T22:59:21.044479Z"
}
},
"server": {
"name": "io.github.biznetai/biznetai-mcp",
"title": "BizNetAI",
"$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
"remotes": [
{
"url": "https://biznetaimcp.consumergenie.net/mcp",
"type": "streamable-http",
"headers": [
{
"name": "Authorization",
"isSecret": true,
"isRequired": true,
"description": "Bearer token — request a key via POST /api/developer-keys (see README), format: Bearer <api_key>"
}
]
}
],
"version": "1.0.0",
"repository": {
"url": "https://github.com/biznetai/biznetai-mcp",
"source": "github"
},
"description": "Routes natural-language shopping queries to merchant storefronts, returns normalized results."
}
}