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yardwisehq.com

Provides access to Yardwise customer reviews, allowing listing, searching, and retrieving detailed review content.

1 endpoint3 known toolsFirst detected August 20, 2026Last detected August 20, 2026

ENDPOINT 1

https://yardwisehq.com/api/mcp

No auth detected

MCP server metadata

Name
yardwise
Version
1.0.0
Capabilities
tools

Known tools 3

list_reviews

List Yardwise reviews, newest first.

Inferred read-only
search_reviews

Full-text search Yardwise reviews by keyword.

Inferred read-only
get_review

Get a single review (summary plus full markdown body) by slug.

Inferred read-only

CONNECT 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.yardwise]
url = "https://yardwisehq.com/api/mcp"
enabled = true
Claude Code

.mcp.json

{
  "mcpServers": {
    "yardwise": {
      "type": "http",
      "url": "https://yardwisehq.com/api/mcp"
    }
  }
}
Claude Desktop

Settings → Connectors → Add custom connector

Name: yardwise
Remote MCP URL: https://yardwisehq.com/api/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": {
    "yardwise": {
      "url": "https://yardwisehq.com/api/mcp"
    }
  }
}
Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code
{
  "servers": {
    "yardwise": {
      "type": "http",
      "url": "https://yardwisehq.com/api/mcp"
    }
  }
}
Generic MCP

Client-specific MCP configuration

{
  "name": "yardwise",
  "transport": "streamable-http",
  "url": "https://yardwisehq.com/api/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.

Indexed

Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.