How to Use the Namsor MCP in Claude Code

Q: What is the command to add Namsor to Claude Code?

Run claude mcp add --transport http namsor -- in your terminal. Remember to place all flags before the server name. The configuration saves automatically to your /.claude.json file.

Pipe Namsor demographic predictions directly into your terminal workflows with Claude Code.

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Connect Namsor MCP to Claude Code

Create your Vinkius account to connect Namsor to Claude Code and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Namsor with Claude Code

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Headless demographic inference via MCP Server

Namsor exposes `predict_gender` and `predict_ethnicity` straight to your command line. Claude Code runs in the background, pulling lists of names from your server logs and hitting the tools without popping open a browser window. You trigger this inside a GitHub Action or a cron job. The CLI agent grabs the data, processes the demographic predictions, and pipes the JSON output into your monitoring stack.

Automate localization in CI/CD

The `predict_country` and `predict_origin` tools let you build geographic routing tests into your deployment pipeline. Your terminal agent reads the incoming user batch and tags them with location metadata before the database migration runs. This happens entirely headless. You write a shell script, hand it to the agent, and it executes the Namsor queries. If the origin predictions look wrong, it fails the build and alerts your SRE team.

CLI-driven name parsing

Raw text files are full of garbage name formats, which `parse_full_name` cleans up instantly. You tell the agent to sanitize a massive CSV dump. It reads the file, splits the names, and writes a clean version to disk. Using `predict_diaspora` on the cleaned data adds another layer of cultural metadata. Your DevOps scripts handle the entire extraction and transformation process via the MCP protocol.

Setup guide

Set up Namsor 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 namsor-mcp with a green status indicator.
3

Start using tools

Ask Claude Code something like "Check my latest Namsor transactions." It will automatically discover and invoke the available Namsor tools.

Terminal

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

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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 Namsor 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": {
    "namsor-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 Namsor. 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.

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Common questions about Namsor MCP in Claude Code

Run `claude mcp add --transport http namsor -- ` in your terminal. Remember to place all flags before the server name. The configuration saves automatically to your `~/.claude.json` file.

Yes. The CLI agent is built for headless environments. You can install it in your container, configure the HTTP transport, and let it process name analytics as part of your automated backend jobs.

Instruct the agent to output the results as raw JSON or CSV. It calls the MCP Server, formats the response from endpoints like `predict_gender`, and prints it to standard output. You just pipe that into `jq` or your next script.

The agent handles the iteration logic natively. You point it at a directory of log files. It extracts the names, loops through the prediction endpoints, and aggregates the data without you touching the keyboard.

The CLI only transmits the specific name strings required for the query. Vinkius routes this traffic through an ephemeral, authenticated endpoint. Your data is processed for the prediction and immediately discarded, requiring only a single token.

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