"Developing an E-commerce ERP" matching MCP servers:

基于Model Context Protocol (MCP) 的A股实时行情查询服务器，支持查询A股实时价格、历史K线数据、财务信息及市场概况。

Enables management of e-commerce operations including products, customers, and orders with full CRUD capabilities, plus data analysis features like sales summaries, top products/customers reports, and inventory tracking.

Provides access to Grips Intelligence e-commerce analytics data through Model Context Protocol. Enables querying domain performance metrics, channel breakdowns, ad spend data, and device analytics for e-commerce businesses.

Exposes ERP data (production orders, inventory, BOM, customers) to any MCP client through a backend-neutral interface, with a mock backend for testing.

Enables AI agents to query and operate on ERP data through a unified tool interface, working across CSV exports, SFTP drop folders, SQLite/ODBC, and optional enterprise APIs. It supports purchase orders, vendors, and inventory lookups while keeping agent-facing tools consistent regardless of backend.

Enables AI assistants to query and operate Dingjie ERP system via natural language, covering procurement, sales, and material management.

Enables querying ERP data via an external API with adaptive caching, and accessing data from Google Sheets or local Excel/CSV files through dual MCP endpoints.

MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.

50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.

Enables MCP clients to search and inspect a catalog of 125 commerce, inventory, and data skills, invoke them with explicit spending limits, and check wallet balances and receipts.

MCP server for converting OEM energy telemetry payloads into ODS-E records and validating them via the odse Python package.

Enables local, read-only product-data checks for reviewing product records, comparing feed snapshots, and comparing dimensions against source rules, returning match or hold decisions without fetching references or modifying feeds.

Resolves messy company, customer, and vendor names across CRM, ERP, and ITSM systems to canonical records using fuzzy matching, preventing AI agents from updating or creating wrong or duplicate records.

It gives Claude Code, Cursor, and Codex structured workflows and an MCP server for building data pipelines with dlt - covering REST API ingestion, transformations, data quality, and exploration.

Minimalistic MCP server that lets AI assistants inspect, quality-check, and clean CSV datasets through tools, resources, and prompts, without needing local file access.

An MCP server that integrates with Hunter.io API to find and verify email addresses using domain and name information.

Material, cell, pack, and supply-chain management with real-time

An MCP server that enables advanced CSV analysis and data visualization using Google's Gemini AI and Plotly. It allows users to perform exploratory data analysis, generate interactive charts, and conduct complex reasoning on tabular data.

Provides Material Requirements Planning (MRP) tools for calculating delivery schedules, determining order needs, and performing MRP period calculations based on inventory levels, forecasts, and order constraints.

A Model Context Protocol server enabling product searches across e-commerce platforms, price history tracking, and product specification-based searches using natural language prompts.