Custom MCP servers
Focused servers organised around capability boundaries, with versioned tool contracts for the systems your agents need to use.
/ mcp server development
MCP servers engineered for production AI agents.
Simatech designs and builds custom Model Context Protocol servers, tool integrations and agent workflows for teams moving beyond isolated AI prototypes.
What is MCP server development?
MCP server development creates a standard interface between AI agents and the tools, data and services they need. Simatech builds that interface as production software: scoped by capability, protected by explicit access controls and integrated into the agent workflow that uses it.
/ what we deliver
The complete MCP integration layer.
Tool registry and integrations
Tool-use and function calling across existing services through MCP, OpenAPI tools and JSON-RPC interfaces.
Agent orchestration
Agent graphs built with LangGraph or LlamaIndex, including the routing and context needed for dependable workflows.
Human-in-the-loop controls
Deterministic policy checks, user-scoped access and human review for actions that should not be left to a model alone.
/ delivery path
From system boundary to production workflow.
- 01
Define the capability boundary
Map the systems, users, tools and permissions involved in the target workflow.
- 02
Build the MCP layer
Implement focused servers, tool contracts, resources and the integration path to each underlying system.
- 03
Connect the agent workflow
Compose tools into an agent graph with explicit routing, checkpoints and failure handling.
- 04
Prepare for production
Add authentication, policy enforcement, evaluation and observability before wider rollout.
/ engagement
A bounded MCP and agentic build-out.
The existing MCP and agentic build-out runs for 3–6 weeks. Named deliverables are MCP servers, a tool registry, an agent graph and human-in-the-loop controls.
Production principles
- Version MCP servers as APIs and keep each server focused on one capability boundary.
- Carry the end user’s identity through every tool call and enforce access outside the model.
- Use scoped session credentials rather than exposing service credentials to an agent.
- Instrument tool calls, failures and agent decisions so the workflow can be evaluated and operated.
Build the MCP layer your agents can rely on.
Bring the workflow, systems and constraints. Simatech will map the build and the production path.
Discuss your MCP project