What runtime dependencies does it require?
Java runtime and Maven build tool are required. It is built as a Java application and configured to work with Claude Desktop.
@ravikalla
基本情報
High-performance XML file comparison with semantic analysis capabilities. Features StAX streaming parser for memory-efficient processing of large XML files (60MB+ tested), order-agnostic semantic comparison, and multiple output formats (text, JSON, Excel). Includes 5 MCP tools fo
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"xml-comparison": {
"command": "java",
"args": [
"-jar",
"/path/to/xml-compare/mcp-xml-comparison/target/xml-comparison-1.0.0.jar"
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
A Model Context Protocol server for XML file comparison with advanced semantic analysis capabilities. It provides five MCP tools for comparing, validating, and analyzing XML files, designed for users who need to compare XML documents in environments like Claude Desktop.
Clone the repository, build with mvn clean package -DskipTests, then configure Claude Desktop with the Java command. After setup, you can compare XML files using natural language through Claude.
Java runtime and Maven build tool are required. It is built as a Java application and configured to work with Claude Desktop.
Sequential comparison (compare_xml_files) is order-sensitive, while semantic comparison (compare_xml_files_semantic) ignores element ordering for a more flexible analysis.
Comparison reports can be output as human-readable Text, structured JSON, or professional Excel spreadsheets.
Yes, the StAX streaming parser has been tested with files over 60MB, making it memory efficient for large documents.
It uses the Model Context Protocol (MCP) via stdin/stdout transport, designed for integration with MCP-compatible hosts like Claude Desktop.
Shared, serverless, conflict-free memory for AI agents: a multi-machine drop-in for the MCP memory knowledge graph.
High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 162 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.

Persistent memory for AI agents. Hosted MCP server with capsule-scoped key/value storage, tags, TTL expiration, bulk ops, and RBAC.

Local-first MCP server that snapshots your project's working state into one context object. Open-core, privacy-first.
Memlord is a remote MCP server available at https://app.memlord.com.
コメント