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AI Engineering

MCP server development for secure agent and tool integration

Model Context Protocol standardizes how intelligent systems discover and use capabilities. GI builds MCP layers for real authentication, permissions and production execution.

Production-first · open standards · auditability · operations
Assess the project technically →AI engineering overview
What a production approach must deliver
  • Well-scoped tools and resources with stable schemas
  • Authentication, roles and server-side authorization
  • Timeouts, retries, rate limits and observability
  • Connect OpenAPI, A2A and existing API landscapes coherently
Related search and project terms
MCP server developmentMCP integrationModel Context Protocol consultingbuild MCP toolsMCP for enterpriseMCP OpenAPI integration
AI Engineering
AI agency & AI engineering partner for production systems→AI agent development that remains controllable in production→Agentic AI development for autonomous but controlled workflows→AI automation for mid-market companies and production teams→AI governance, audit trails and human oversight for agents→Self-hosted AI and private LLMs for sensitive data and controlled operations→AI agency, freelancer or in-house team: which model fits when?→Agentic AI or classic workflow automation?→MCP or direct API integration: which interface should you use?→