How to Use the Namsor MCP in Windsurf

Windsurf runs Namsor analytics to predict demographic data autonomously without prompting every step.

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Connect Namsor MCP to Windsurf

Create your Vinkius account to connect Namsor to Windsurf 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 Windsurf

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Claude

Perplexity

Autonomous demographic pipelines in Windsurf

Namsor's `predict_gender` and `predict_ethnicity` tools sit right inside your IDE context. Cascade looks at your raw user data, decides which prediction endpoints to hit, and runs the entire batch. You just tell the agent to build a diversity report. It doesn't stop to ask permission for every API call. The agent chains `parse_full_name` to clean up messy inputs before feeding them to `predict_origin`. You get structured demographic JSON dumped straight into your project files.

Macro-level origin tracking via MCP Server

The `predict_country` tool maps names to likely residency locations. When your workspace contains raw signup logs, Cascade reads the files and tags each user row with geographic metadata. This cuts out the manual script writing you usually do for localization tasks. Your agent builds the mapping logic, fires the requests to the endpoints, and formats the output into a clean CSV while you watch.

Cultural context for marketing

Hitting `predict_diaspora` gives you insight into cultural assimilation layers. Cascade can read your email campaign templates, analyze the target recipient list, and suggest localization tweaks based on the returned data. Instead of guessing who your users are, you let the AI handle the heavy lifting of demographic inference. It pulls the insights and injects them directly into your marketing automation code.

Setup guide

Set up Namsor MCP in Windsurf

Prerequisites

Windsurf IDE installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP configuration

Click the Cascade assistant icon in the sidebar, then click the hammer icon (🔨) at the top of the panel. Select "Configure" to open ~/.codeium/windsurf/mcp_config.json.
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

Refresh MCPs

Go back to the hammer icon (🔨) in Cascade and click "Refresh". Windsurf will detect the new server. No full restart is needed — the connection is hot-reloaded.
4

Verify in Cascade

Start a new Cascade conversation and ask something like "Show my Namsor payment history." If connected, Cascade will call the Namsor tools directly. You will see a green dot next to the server name in the MCP panel.

mcp_config.json

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

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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 Windsurf

Open your IDE settings and navigate to the Cascade MCP Servers UI. You can add the server configuration directly to your `mcp_config.json` under the `mcpServers` key. Click refresh in the panel, and Cascade auto-discovers the tools immediately.

Yes. Cascade excels at multi-step execution. It will naturally call `parse_full_name` first, then pass the cleaned strings into `predict_ethnicity` or `predict_gender` without needing a separate prompt for each step.

The tools process the names you feed them. Cascade manages the looping logic. If you have a massive JSON file of users, the agent writes a quick script to iterate through them and hit the Namsor endpoints.

The API returns a confidence score alongside the prediction. Your agent reads that metadata. You can tell Cascade to ignore any results from `predict_origin` that fall below a certain threshold.

The server only processes the raw text strings of user names you pass to it. Vinkius runs this integration inside an ephemeral V8 Isolate Sandbox. Once the prediction returns to your IDE, the sandbox wipes the memory clean.

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