We are seeking an experienced software engineer to build a Model Context Protocol (MCP) server for our existing optimization engine, which is focused on supply and demand planning (inventory management, demand forecasting, purchase order automation).
The MCP server will enable AI agents to:
Configure and trigger optimization runs by setting parameters (e.g., safety stock levels, reorder points, purchasing rules).
Retrieve optimization model results.
Interpret optimization outputs against predefined business conditions and thresholds.
The goal is to make our optimization engine easily accessible to AI agents via a standardized MCP interface.
Responsibilities:
Develop a lightweight MCP server using Python or TypeScript (preferred)
Define MCP-compliant tools (functions) to interact with our optimization engine
Implement authentication and access control mechanisms
Ensure robust and secure communication (JSON-RPC over HTTP/SSE)
Provide thorough documentation of the MCP server setup, deployment, and usage
Required Skills:
Strong experience with Python or TypeScript
Familiarity with JSON-RPC, REST APIs, or similar integration standards
Prior experience or familiarity with MCP or similar standards (OpenAI plugin interfaces, JSON-RPC, Language Server Protocol)
Experience developing secure, scalable API services
Nice to Have:
Familiarity with supply chain planning or optimization problems
Experience with AI/LLM integrations (OpenAI, Anthropic, or similar)
Prior experience with SaaS applications
Deliverables:
Fully functional MCP server integrated with our optimization engine
Documentation of MCP tools, usage examples, and API reference
Basic testing suite demonstrating integration and usage
Timeline:
Initial MVP within 4-6 weeks, with possible extensions based on success.
Application:
Please include:
Brief description of your relevant experience
Examples of similar integrations or API-driven projects you've completed
Your availability and proposed timeline for completion
We look forward to collaborating with you!
