Agents & orchestration
Agents that carry out real tasks in your tools, connected via MCP, the standard that saves you from rewiring everything each time you switch models.
A chatbot answers, an agent acts. To act, an agent has to be plugged into your tools, and that's what MCP is for: think of it as the USB-C of your software. You write the connection once, and it works with Claude, GPT, Gemini or a private model installed in-house. In eighteen months it has become the standard followed by Anthropic, OpenAI, Google and Microsoft, and above all MCP spares you one trap: depending on a single vendor. And since the connector can run inside your infrastructure, your access stays with you, ready to feed a private model when confidentiality demands it. On this foundation, I build agents that take a request, decide and act, and when the task calls for it, several specialized agents coordinate, with an orchestrator and guardrails everywhere.
Key facts
24/7
the agent acts in your tools, day and night, no queue
once
one MCP connection written once, reused with Claude, GPT or a private model
on-site
the MCP connector can run in your own infra, right next to your systems
What I build
Your tools connected via MCP
MCP is the USB-C of your software: you connect your CRM, emails, databases and APIs once, and it then works with Claude, GPT or a private model. You switch models without redoing everything, and the connector can stay in-house.
MCP · No vendor lock-in · Sovereignty · Sovereign MCP server
Tool-using business agents
An agent that answers, decides and executes real actions in your tools through these connections, and escalates to a human when needed.
Tool actions · Human escalation · Support
Multi-agent orchestration
Several specialized agents that coordinate on complex tasks, with an orchestrator and guardrails.
Multi-agent · Coordination · Guardrails
The promise
An agent that acts, not a chatbot that talks.
Before / after
An integration to redo each time you switch models
One MCP connection written once, reusable with any model
Tools that don't talk to each other
An agent that acts across every tool
The stack
MCP
LangGraph
Claude
Tool use
n8n
Python
TypeScript
Webhooks
Straight answers
What is MCP, in plain terms?
MCP is the standard that plugs an AI into your software, a bit like USB-C plugs in any device. In practice, I connect your tools once, and the same connection works with Claude, GPT, Gemini or a private model. Adopted in under two years by the major players and handed to the Linux Foundation in late 2025, it has become the standard way to connect AI, which protects you the day you want to switch vendors.
What's the difference between a chatbot and an AI agent?
A chatbot answers questions. An agent acts: it reads your tools, decides, executes an action (creating a ticket, sending a follow-up, updating the CRM) and escalates to a human when the situation calls for it.
Can the agent do anything it wants in my tools?
No. Every agent has a defined scope of actions, hard limits, and human approval on sensitive or irreversible actions. Guardrails are designed before the agent, not after.
How much does an AI agent in production cost?
It depends on scope, and I put a number on it on the first call, free of charge. On the running side, I architect so the token bill stays under control: the right model in the right place, caching, spending limits.
Do I need several agents?
Rarely at the start. One well-equipped agent covers most cases. We move to multi-agent setups when the task truly demands it, with an orchestrator and guardrails: it's a means, not a marketing pitch.
Contact
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