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Connect LLM XML Tag Parser to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Turn messy model outputs into clean, structured data.

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Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 3 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through LLM XML Tag Parser.

  1. 01

    Extract all tags

    This capability pulls every top-level occurrence of a specific XML tag from the text. It's useful when a model provides multiple separate blocks of the same type.

  2. 02

    Extract single tag

    This capability finds and returns only the first instance of a specific XML tag. Use this to grab a single reasoning block or a specific answer.

  3. 03

    Validate tag integrity

    This capability checks if your XML tags are properly balanced and nested. It helps catch errors where a model fails to close a tag correctly.

Real work

What teams actually run

01

Reasoning Isolation

Pull the contents of a <think> tag to hide the model's internal logic from the end user.

02

Data Extraction

Grab specific data points wrapped in custom tags for use in other applications.

03

Output Validation

Check if an agent's response is structurally sound before passing it to a parser.

04

Batch Processing

Retrieve all occurrences of a tag when a model generates a list of items in XML format.

One connector, every AI

LLM XML Tag Parser works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put LLM XML Tag Parser to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

715ms average. Fast in production.

LLM XML Tag Parser is checked daily against the live service.

Daily averagePeak 834ms
Oct 3Today
Fastest day
543ms
Slowest day
834ms
14-day trend
Improving-8%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 3 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of LLM XML Tag Parser, so you can see the experience inside your AI.

It does not authenticate your account with LLM XML Tag Parser. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

LLM XML Tag Parser Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_w58Iyf6iS1Dvk9wxnoCriPGJu7Dnb9x0GKyijsMS/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — LLM XML Tag Parser capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "llm-xml-tag-parser-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_w58Iyf6iS1Dvk9wxnoCriPGJu7Dnb9x0GKyijsMS/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up LLM XML Tag Parser in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work LLM XML Tag Parser owners hand off.

This MCP is for developers and power users building workflows that rely on structured model outputs.

  • 01

    AI Engineers

    They hand off raw model strings to this MCP to clean data for databases or APIs.

  • 02

    Workflow Automators

    They use it to parse reasoning steps from agents to trigger specific logic.

  • 03

    Data Analysts

    They extract specific data points from large batches of model-generated text.

FAQ

Questions LLM XML Tag Parser owners ask.

  • 01

    What can this MCP do with XML tags?

    It extracts content from specific tags, finds all instances of a tag, and validates that tags are properly nested and balanced.

  • 02

    Does it work with Claude?

    Yes, it is specifically designed to handle outputs from models that use XML tags for structure, such as Claude.

  • 03

    How does it handle nested tags?

    The MCP uses depth tracking to ensure it correctly identifies the boundaries of nested XML structures.

  • 04

    Which AI clients can use this?

    Any MCP-compatible client like Claude, Cursor, Windsurf, or VS Code can use these capabilities.

  • 05

    Do I need to host this myself?

    No, Vinkius hosts and manages the MCP so it is ready to use immediately after you connect.

  • 06

    How does the parser handle nested tags?

    The parser uses an integer depth counter. When it encounters an opening tag, it increments the counter; when it finds a closing tag, it decrements it. This ensures that extract_all_tags correctly identifies fully closed pairs even in complex structures.

  • 07

    Can I use this to validate if my prompt output is well-formed?

    Yes, by using the validate_tag_integrity capability, you can check if every opening tag has a corresponding closing tag and verify that the nesting depth is balanced.

  • 08

    What happens if a tag is not found?

    If you use extract_single_tag and the target tag does not exist in the input string, the capability will return null for the extracted content.

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