How to Use the N-Gram Frequency Engine MCP in Windsurf

Q: How do I install the N-Gram Frequency Engine MCP Server in Windsurf?

Edit your /.codeium/windsurf/mcpconfig.json file. Add the server details under the mcpServers array. You can also use the Settings UI to configure Cascade directly.

Windsurf Cascade runs deterministic text analysis to extract exact N-gram counts without wasting tokens.

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Connect N-Gram Frequency Engine MCP to Windsurf

Create your Vinkius account to connect N-Gram Frequency Engine 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 N-Gram Frequency Engine with Windsurf

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Perplexity

Deterministic Counting for Windsurf

The `extract_ngram_frequencies` tool parses massive text files and returns exact unigram, bigram, and trigram counts. Cascade invokes this tool to bypass probabilistic guessing. LLMs are terrible at math and frequency counting. This MCP Server gives your agent hard numbers. You set a goal to analyze a specific corpus. Cascade reads the context, plans the extraction, and runs the tool autonomously. It strips punctuation, normalizes cases, and maps the frequencies. You get the final JSON distribution without writing the parsing logic yourself.

Token-Efficient Text Analysis

Sending gigabytes of text into a context window burns tokens and guarantees hallucinations. This MCP Server processes the raw text locally. It returns only the dense statistical distribution. Your AI client sees the top 50 trigrams instead of a million raw words. That saves API costs. It also forces the model to base its linguistic insights on actual data rather than predicted next tokens.

Autonomous Multi-Step Processing

Frequency extraction is rarely the final step. Cascade chains the output of `extract_ngram_frequencies` directly into your next task. It pulls the bigram counts and immediately writes a script to visualize them. You do not need to prompt each phase. The agent sees the exact phrase counts, recognizes the distribution patterns, and generates the required charts or reports. The entire pipeline runs end-to-end.

Setup guide

Set up N-Gram Frequency Engine 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 N-Gram Frequency Engine 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 N-Gram Frequency Engine payment history." If connected, Cascade will call the N-Gram Frequency Engine tools directly. You will see a green dot next to the server name in the MCP panel.

mcp_config.json

{
  "mcpServers": {
    "n-gram-frequency-engine-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Common questions about N-Gram Frequency Engine MCP in Windsurf

Edit your `~/.codeium/windsurf/mcp_config.json` file. Add the server details under the `mcpServers` array. You can also use the Settings UI to configure Cascade directly.

Yes. Cascade auto-discovers the extraction tool the moment you connect. It will plan and execute frequency counts across your datasets without asking for step-by-step permission.

The tool uses streaming string processing to avoid memory bloat. You can point it at massive corpora. It slices words into sliding windows and builds frequency maps without loading everything into RAM at once.

Writing a custom script takes time and interrupts your workflow. This MCP implementation gives Cascade immediate access to deterministic counts. Your agent gets the data it needs instantly.

Your raw text corpora never leave your local machine. The server processes the files locally and only passes the final frequency JSON back to your agent. No third-party API intercepts your linguistic data.

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