Analytics
smartvisuals.io
Provides tools to search, list, and retrieve SmartVisuals Power BI custom visual catalog entries, metadata, and binding examples.
ENDPOINT 1
https://www.smartvisuals.io/mcp
MCP server metadata
- Name
- SmartVisuals Catalog
- Version
- 1.0.0
Known tools 4
get_visualReturn the full catalog entry for one SmartVisuals Power BI custom visual, including its GUID, data roles (field wells), version, description, use cases, free-tier limits, premium features and diagnostic flags.
Inferred read-onlyget_binding_exampleReturn the PBIR (Power BI Report) layout snippet and binding notes for a SmartVisuals visual.
Inferred read-onlyCONNECT WITH APPROVAL
Client installation
Review this server and its permissions before adding it. Secret placeholders must be set locally.
Codex
~/.codex/config.toml
[mcp_servers.smartvisuals-catalog]
url = "https://www.smartvisuals.io/mcp"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"smartvisuals-catalog": {
"type": "http",
"url": "https://www.smartvisuals.io/mcp"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: smartvisuals-catalog
Remote MCP URL: https://www.smartvisuals.io/mcp
Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.
Cursor
.cursor/mcp.json
{
"mcpServers": {
"smartvisuals-catalog": {
"url": "https://www.smartvisuals.io/mcp"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"smartvisuals-catalog": {
"type": "http",
"url": "https://www.smartvisuals.io/mcp"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "smartvisuals-catalog",
"transport": "streamable-http",
"url": "https://www.smartvisuals.io/mcp"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
TRUST AND VERIFICATION EVIDENCE
Loading Trust v2 evidence…
Checking the associated registrable domain. The BuiltWith key remains server-side.
Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.