How to Use the ShowAPI / 易源数据 MCP in Claude Code

Q: How do I call ShowAPI / 易源数据 with Claude Code?

You connect the server using claude mcp add --transport http . Once configured, you access tools by calling their functions directly in your script or job definition.

Run API pipelines headlessly with Claude Code and ShowAPI / 易源数据.

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Connect ShowAPI / 易源数据 MCP to Claude Code

Create your Vinkius account to connect ShowAPI / 易源数据 to Claude Code — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup ShowAPI / 易源数据 with Claude Code

Ask AI about this MCP

ChatGPT

Claude

Perplexity Vinkius runs on Gemini

Gemini

Grok

Build CI/CD data validation scripts.

You can script complex checks. For example, you write a job that calls `get_stock_info` to check current prices and then pipes the result into `get_currency_rates` to see how those funds translate globally. It's all done in a single shell command.

Process multi-lingual content via pipe.

Need to process user comments? Run a script that first uses `translate_text` on incoming text, then pipes the translated output into a tool like `get_english_dictionary` for validation. This keeps all your logic contained in the terminal.

Automate information gathering via cron jobs.

Schedule nightly reports by running a job that calls `get_weather` for multiple locations, then aggregates the data using shell scripting features. The output is pure JSON or CSV, perfect for logging into a database.

Setup guide

Set up ShowAPI / 易源数据 MCP in Claude Code

Prerequisites

Claude Code CLI installed (npm install -g @anthropic-ai/claude-code)
Active Vinkius subscription with a valid endpoint token

1

Run the add command

Open your terminal and run the command shown on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com. Use --scope user to make it available across all projects.
2

Verify the connection

Start a Claude Code session and type /mcp to list connected servers. You should see showapi-mcp with a green status indicator.
3

Start using tools

Ask Claude Code something like "Check my latest ShowAPI / 易源数据 transactions." It will automatically discover and invoke the available ShowAPI / 易源数据 tools.

Terminal

claude mcp add --transport http showapi-mcp https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Get your connection token →

Prerequisites

Claude Code CLI installed
Active Vinkius subscription with a valid endpoint token

1

Open the config file

Create or edit .mcp.json in your project root for project-level scope, or ~/.claude.json for user-level scope.
2

Add the ShowAPI / 易源数据 MCP

Paste the JSON snippet shown on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Restart Claude Code

Start a new Claude Code session. Type /mcp to confirm the server is connected. The tools will be automatically available in your conversation.

.mcp.json

{
  "mcpServers": {
    "showapi-mcp": {
      "type": "url",
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ShowAPI / 易源数据. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

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Single dashboard

One

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Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about ShowAPI / 易源数据 MCP in Claude Code

You connect the server using `claude mcp add --transport http `. Once configured, you access tools by calling their functions directly in your script or job definition.

Yes. Since it's designed for CI/CD pipelines, the server handles necessary transports like HTTP and STDIO, ensuring the output is clean and machine-readable in any environment.

The core data types here are geographical coordinates or text strings. When running scripts that use `get_ip_lookup`, always ensure the output is masked before it leaves the container environment.

Of course. Since the setup supports running in headless environments, you can easily include the MCP Server connection and all necessary calls within your Dockerfile entry point or build script.

The MCP Server wraps authentication and standardized error handling. You simply call `get_jokes` by its function name, instead of managing multiple separate API endpoints and key headers.

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