LLM XML Tag Parser

LLM XML Tag Parser MCP Connector for Claude

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Extract and validate content within XML-style tags from LLM outputs.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner

The LLM XML Tag Parser MCP server provides a deterministic way to parse structured data embedded in unstructured text. It is specifically designed for handling the output of models like Claude that use XML tags (e.g., , ) to separate reasoning from final responses. Using robust regex-based extraction and depth tracking, it can handle nested tags and verify structural integrity. You can use extract_single_tag to find specific blocks, extract_all_tags to retrieve all instances of a tag, or validate_tag_integrity to ensure your XML structure is balanced.

xmlregexparsingclaudestructured-data

3 tools expose this connector's capabilities to your AI agent.

extract_all_tags

Extract all top-level occurrences of a specific XML tag

extract_single_tag

Extract the first occurrence of a specific XML tag

validate_tag_integrity

Validate the integrity of XML tag nesting

See how to talk to your AI agent using LLM XML Tag Parser.

Extract the reasoning from this output: <think>I should check the weather.</think><answer>The weather is sunny.</answer>

I should check the weather.

Check if these tags are balanced: <data><item>1</item></data>

The tag integrity is valid, and the nesting depth was 1.

Find all instances of the 'note' tag in: <note>First</note><other>Text</other><note>Second</note>

['First', 'Second']

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.

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