ERP MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ERP MCP ServerGet stock level for product 42"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
ERP MCP Server
A Python-based backend server demonstrating the deployment of custom business tools using the Model Context Protocol (MCP). This project leverages Anthropic's FastMCP framework to effortlessly expose standard enterprise data sources (Orders, Inventory, and Vendors) as structured tools for LLM consumption.
For demonstration pursposes, It is designed to read localized mock databases and seamlessly host them over an MCP-compliant transport layer.
🚀 Key Features
FastMCP Integration: Uses the high-level FastMCP wrapper to automatically generate schemas and expose functions as LLM-callable tools.
Granular ERP Modules: Separate endpoints to pull distinct, isolated datasets for Orders, Inventory quantities, and Vendor metadata.
JSON-backed Persistence: Simulates production database interactions using lightweight, predictable JSON flat files.
Robust Error Handling: Returns well-formed JSON error schemas to gracefully inform LLMs when lookups fail.
Related MCP server: Small Business MCP Server
🛠️ Exposed Tools
The server dynamically broadcasts four main developer tools to any connected client:
get_sales_order(order_id: int): Fetches precise sales order data including statuses, pricing, and transactional lines.get_stock(product_id: int): Checks inventory tables for real-time stock levels and reorder parameters.get_vendor(vendor_id: int): Looks up explicit business credentials, risk profiles, and payment cycles for a single partner.get_vendors_information(): Pulls the comprehensive registry of all active vendors for broad analytical overviews.
Installation
Add the required dependencies individually using uv (this will automatically fetch the latest versions):
uv add gradio
uv add "mcp[cli]"
uv add openaiTo Run The server
uv run mcp run server.py --transport streamable-http
This server cannot be deployed
Maintenance
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Let AI agents query data and act across all your business apps via MCP.
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Unified MCP Server is a remote MCP connector for AI agents and vertical AI products that provides access to 22,000+ authorized SaaS tools across 400+ integrations and 24 categories directly inside LLMs (Claude, GPT, Gemini, Cohere). Tools operate only on explicitly authorized customer connections, enabling agents to safely read and write against live third-party systems.
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