AI Agents & MCP Development
AI agents that do not just answer — they execute tasks, connected to your systems through the Model Context Protocol.
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We build agents that plan steps, call tools, and complete real tasks across multiple systems. We use the Model Context Protocol (MCP) for a standardized, secure connection between the agent and your data and APIs, with clear limits on what it is allowed to do.
What's included
How we work
Define task & tools
We define what the agent must achieve, which tools it needs, and where the limits are.
MCP integration
We build or connect MCP servers so the agent has controlled access to data and APIs.
Guardrails & testing
We add permission scopes, validation, and approvals, and test against controlled scenarios.
Deployment & observability
We deploy the agent to production with full tracing, alerting, and cost monitoring.
FAQ
What is MCP and why do you use it?
The Model Context Protocol is an open standard that standardizes how an AI model connects to tools and data sources. It enables reusable, secure integrations instead of custom code per model.
How autonomous is the agent?
You set the level of autonomy. Low-risk actions run automatically, while sensitive ones require approval. Every scope is explicitly defined, so the agent does nothing outside its allowed limits.
What happens if the agent takes a wrong action?
Critical actions go through approval and, where feasible, are reversible. Full tracing shows what the agent reasoned and did at each step, so we can fix the logic quickly.
