MCP server

Shoe Fit Checker

io.github.anburan-tech/shoe-fit-checker

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Bounded footwear fit checks for a specific shoe, person, and intended use.

Working at last checkAbout 1,062 tokens per request once connected1 tools

Source

https://shoe-fit-checker.onrender.com/mcp

At a glance

Type: MCP server
Publisher: Not verified
Status: Working at last check
Tools: 1
Token cost: About 1,062 tokens per request
Sets up in: Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok
Last checked: 26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to Cursor Add to VS Code VS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http shoe-fit-checker https://shoe-fit-checker.onrender.com/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.shoe-fit-checker]
url = "https://shoe-fit-checker.onrender.com/mcp"

Gemini CLI

{"mcpServers":{"shoe-fit-checker":{"httpUrl":"https://shoe-fit-checker.onrender.com/mcp"}}}

Cursor

{"mcpServers":{"shoe-fit-checker":{"url":"https://shoe-fit-checker.onrender.com/mcp"}}}

VS Code

{"servers":{"shoe-fit-checker":{"type":"http","url":"https://shoe-fit-checker.onrender.com/mcp"}}}

Antigravity

agy mcp add shoe-fit-checker https://shoe-fit-checker.onrender.com/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"shoe-fit-checker","server_url":"https://shoe-fit-checker.onrender.com/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"shoe-fit-checker","server_url":"https://shoe-fit-checker.onrender.com/mcp"}

Tools

check_footwear_fit ~1062 tokens
Use for a specific finished footwear product and the person's reported interaction. English is the primary consumer-language coverage; full Chinese interpretation is deferred. Without a complete approved canonical request, the three limited prototype paths are activity-related compression or numbnes

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