FAQ

Frequently Asked Questions

What is an MCP server?

MCP stands for Model Context Protocol, an open standard developed by Anthropic. An MCP server is a service that exposes tools, resources, and prompts to AI agents in a standardized way. AI assistants like Claude Desktop, ChatGPT Desktop, and Antigravity can connect to MCP servers to extend their capabilities beyond conversation — letting them call specialized services, query databases, or in Solvicus's case, run mathematical optimization solvers.

What is mathematical optimization?

Mathematical optimization is the process of finding the best solution to a problem from a set of possible alternatives, subject to constraints. Given a set of variables, an objective (e.g. minimize cost, maximize profit), and constraints (e.g. capacity limits, budget), an optimization solver computes the provably optimal — or near-optimal — solution. It is used everywhere from airline scheduling and supply chain planning to portfolio management and staff rostering.

Why should I use mathematical optimization via an MCP server?

AI agents are remarkably good at understanding your situation, interpreting your data, and translating it into structured input — but they are not designed to solve combinatorial or linear optimization problems efficiently. Modern solvers are purpose-built for this: they use decades of algorithmic research (simplex method, branch-and-bound, cutting planes) to find optimal solutions to problems with thousands of variables and constraints in seconds.

Solvicus bridges the gap: the AI agent handles the natural-language interface and data translation; the solver handles the math. You get the best of both worlds — the conversational ease of an AI assistant and the provably optimal results of a dedicated solver.

What are examples where I should use Solvicus?

• Staff scheduling: given shift preferences, availability, labor laws, and demand forecasts, find the schedule that minimizes cost while respecting all constraints.
• Logistics & routing: optimize delivery routes across a fleet of vehicles to minimize distance or time.
• Production planning: determine what to produce, how much, and when — balancing inventory costs, machine capacity, and customer demand.
• Portfolio optimization: allocate a budget across assets to maximize expected return for a given risk level.
• Procurement & diet planning: select a combination of suppliers or ingredients that meets quality or nutritional requirements at minimum cost.

What types of optimization problems can Solvicus solve?

Solvicus currently supports linear programming (LP) and mixed-integer linear programming (MILP / MIP) problems. These cover the vast majority of real-world planning and scheduling scenarios. Support for additional problem types such as quadratic programming is on the roadmap.

Do I need to know how to write optimization models?

No — and that is the whole point. You describe your problem in plain language to your AI agent, and the agent translates it into the formal input Solvicus needs. You do not need to learn modeling languages like LP or MPS format, and you do not need to understand how solvers work internally.

Is my data secure?

Yes. Optimization data (variables, constraints, solutions) is processed temporarily and stored for at most 14 days for support purposes, then automatically deleted. We never use your data to train AI models. Our infrastructure runs on Google Cloud within the EU.

Your account information (name and email address) is managed by Zitadel, an identity and access management product of CAOS AG, a Switzerland-based company. Switzerland is recognised by the EU Commission as providing an adequate level of data protection. See our Privacy Policy for full details.

How do I get started?

Register for a free account, copy your personal server URL and access token from the dashboard, and add the Solvicus MCP server to your AI client of choice — Claude Desktop, ChatGPT Desktop, or Antigravity. The full setup takes about two minutes. See the Integrations section for step-by-step instructions.