Solr MCP

#!/usr/bin/env python3 """ Script to process markdown files, splitting them by section headings and preparing them for indexing in Solr with vector embeddings. """ import argparse import json import os import re import sys from datetime import datetime from typing import Dict, List, Tuple import frontmatter def extract_sections(markdown_content: str) -> List[Tuple[str, str]]: """ Extract sections from a markdown document based on headings. Args: markdown_content: The content of the markdown file Returns: List of tuples (section_title, section_content) """ # Split by headers (# Header) header_pattern = r'^(#{1,6})\s+(.+?)$' lines = markdown_content.split('\n') sections = [] current_title = "Introduction" current_content = [] for line in lines: header_match = re.match(header_pattern, line, re.MULTILINE) if header_match: # Save previous section if current_content: sections.append((current_title, '\n'.join(current_content).strip())) current_content = [] # Start new section current_title = header_match.group(2).strip() else: current_content.append(line) # Add the last section if current_content: sections.append((current_title, '\n'.join(current_content).strip())) return sections def convert_to_solr_docs(sections: List[Tuple[str, str]], filename: str, metadata: Dict) -> List[Dict]: """ Convert markdown sections to Solr documents. Args: sections: List of (title, content) tuples filename: Original filename metadata: Metadata from frontmatter Returns: List of documents ready for Solr indexing """ documents = [] for i, (title, content) in enumerate(sections): # Skip empty sections if not content.strip(): continue doc = { "id": f"{os.path.basename(filename)}_section_{i}", "title": title, "text": content, "source": filename, "section_number": i, "date_indexed": datetime.now().isoformat(), "tags": metadata.get("tags", []), "category": metadata.get("categories", []) } # Add any additional metadata for key, value in metadata.items(): if key not in ["tags", "categories"] and key not in doc: doc[key] = value documents.append(doc) return documents def process_markdown_file(file_path: str, output_file: str = None): """ Process a markdown file, splitting it into sections and converting to Solr documents. Args: file_path: Path to the markdown file output_file: Path to save the JSON output (if None, prints to stdout) """ # Read and parse markdown with frontmatter with open(file_path, 'r', encoding='utf-8') as f: post = frontmatter.load(f) # Extract frontmatter metadata and content metadata = dict(post.metadata) content = post.content # Extract sections sections = extract_sections(content) # Convert to Solr documents documents = convert_to_solr_docs(sections, file_path, metadata) # Output if output_file: with open(output_file, 'w', encoding='utf-8') as f: json.dump(documents, f, indent=2) print(f"Processed {file_path} into {len(documents)} sections and saved to {output_file}") else: print(json.dumps(documents, indent=2)) print(f"Processed {file_path} into {len(documents)} sections", file=sys.stderr) if __name__ == "__main__": parser = argparse.ArgumentParser(description="Process markdown files for Solr indexing") parser.add_argument("file", help="Path to the markdown file") parser.add_argument("--output", "-o", help="Output JSON file path") args = parser.parse_args() process_markdown_file(args.file, args.output)