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MCP 工具与服务目录

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正式条目

87,640

可复制安装

36,828

最近生成

2026-05-22

文档知识HTTP

全面解析Ergut MCP Logseq ServerMCP Server的核心功能、安装配置和实用案例。作为顶级Model Context Protocol服务器,Ergut MCP Logseq Server能让AI助手访问实时数据、执行操作,为您提供更智能的工作体验和自动化解决方案。

安装状态

已补齐

命令预览

npx @modelcontextprotocol/inspector uv --directory /path/to/mcp-logseq run mcp-logseq

文档知识未说明

Enables comprehensive interaction with ERPNext systems through natural language, providing secure access to any document type (customers, items, invoices, etc.) with enterprise-grade permission controls and audit logging.

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Enables access to Japan's official government statistics portal (e-Stat) API to search, retrieve, and analyze statistical data including census data, economic indicators, and demographic information across 17 statistical fields.

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Bridges Ethereum JSON-RPC queries from Geth nodes to the Model Context Protocol ecosystem, exposing blockchain operations as MCP tools. Enables AI models and applications to securely interact with Ethereum data including blocks, transactions, balances, and advanced debug functions through schema-validated access.

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A minimal Model Context Protocol (MCP) server that fetches the current Ethereum (ETH) price in USD. Data source: the public CoinGecko API (no API key required). This MCP is designed to simulate malicious behavior, specifically an attempt to mislead LLM to return incorrect results.

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A comprehensive Model Context Protocol (MCP) server for EVE Online traffic, navigation, and system information using both the official ESI API and SDE data.

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A Model Context Protocol server that allows AI assistants like Claude to interact with Evernote, enabling them to create, search, read, and manage notes through natural language.

文档知识未说明

Enables Claude to interact with Evernote notes and notebooks, supporting full-text search, note operations (create, read, update, delete), and multiple output formats for both International Evernote and Yinxiang Biji.

文档知识未说明

A Model Context Protocol (MCP) server that provides access to EVE University Wiki content with automatic Wayback Machine fallback for enhanced reliability. This server enables AI assistants to search, retrieve, and explore EVE Online knowledge from the comprehensive EVE University Wiki, making it a

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Enables efficient reading, analyzing, and querying of Excel, CSV, and JSON files with support for chunked processing, column/field filtering, and streaming for large datasets. Supports multiple transport protocols (stdio, HTTP, SSE) for flexible integration.

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Enables users to analyze local Excel and CSV files through natural language queries and a web dashboard while keeping data local. It supports saving specific analyses as reusable tools and building a custom analytics toolkit within Claude Desktop.

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An MCP server that allows LLMs to read, analyze, and interact with Excel files through file operations, data discovery, and comprehensive analysis tools.

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An MCP server for manipulating Excel files that features a headless engine for real-time formula calculation and data validation. It enables users to create, read, and manage workbooks, sheets, and charts without requiring Microsoft Excel installed.

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An MCP server for reading, writing, and analyzing Excel files using Python, pandas, and openpyxl. It enables tasks such as managing multiple worksheets, performing structural data analysis, and creating new files from JSON data.

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Inspect and remove EXIF metadata locally through MCP tools. Supports reading EXIF, detecting GPS, summarizing privacy risks, and stripping EXIF from images.

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A lightweight server built with FastMCP and SQLite for managing personal finances. It allows users to add, list, and summarize expenses by category through MCP-compatible clients.

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Enables users to track and manage daily expenses through SQLite storage, supporting operations like adding, updating, deleting expenses, calculating totals by category, and filtering expenses by date range or category.

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Parses PDF receipts to extract grocery and shopping expenses, automatically categorizes items using smart rules and LLM fallback, and stores them in a local SQLite database for querying purchase history and spending patterns.