What They Are and Why They Matter for Business Central
Introduction
The world of enterprise
software is being reshaped by AI agents. Imagine telling your ERP system, in
plain English, to look up a customer, check inventory levels, or create a sales
order. No clicking through menus, no memorizing page names, just a natural
conversation that gets work done.
In this first post of
our four-part series, we cover the foundational concepts: what AI agents are,
how the Model Context Protocol (MCP) works, and why these matter for anyone
working with Dynamics 365 Business Central.
What Are AI Agents?
An AI agent is a
software program powered by a large language model (LLM) that can understand
instructions, reason about tasks, and take actions on your behalf. Unlike a
simple chatbot that only generates text, an agent can interact with external
systems, call APIs, retrieve data, and execute workflows autonomously or
semi-autonomously.
Key Characteristics
•
Reasoning: They understand natural language, maintain
context across a conversation, and can break complex requests into smaller
steps.
•
Tool Use: They can call external tools, APIs, databases,
and services to perform real work, not just talk about it.
•
Planning: They decompose a high-level goal (e.g., “create
a sales order”) into sub-tasks (find customer, find item, create header, add
line).
•
Human-in-the-Loop: For sensitive actions like creating or deleting
records, agents ask for explicit user confirmation before proceeding.
Agents vs. Chatbots vs. Copilots
|
|
Chatbot |
Copilot |
Agent |
|
Interaction |
Q&A only |
Suggests
& assists |
Plans &
executes |
|
Tool
Access |
None |
Limited |
Full (APIs,
DBs) |
|
Autonomy |
None |
Low |
High (with
guardrails) |
|
Example |
FAQ bot |
GitHub
Copilot |
BC MCP Agent |
Why Agents Matter for Business Central
Business Central is a
powerful ERP, but navigating its rich feature set often requires training and
familiarity. AI agents lower the barrier by letting users interact with BC
through conversation. A project manager can ask for a budget-vs-actual report, a
warehouse worker can check stock levels, and a finance lead can review
outstanding invoices, all without opening a single BC page.
The critical enabler
for this is a standardized way for agents to discover and call BC’s
capabilities. That is exactly what the Model Context Protocol provides.
What Is the Model Context Protocol (MCP)?
MCP is an open API
standard, originally championed by Anthropic, that defines how AI applications
discover, describe, and invoke operations on external services. Think of it as
a universal adapter between any AI client (Claude, Copilot, a custom agent) and
any backend system (Business Central, GitHub, Salesforce, etc.).
How MCP Works
The protocol follows a
four-step pattern:
1. Discovery – The AI
client connects to an MCP server and asks: “What tools do you offer?”
2. Description – The MCP
server responds with a list of tools, their parameters, and plain-English
descriptions.
3. Invocation – Based on
the user’s request, the AI selects the right tool, fills in parameters, and
calls it.
4. Response – The MCP
server executes the operation and returns the result to the AI client.
This self-describing,
plug-and-play architecture means agents do not need hardcoded knowledge of
every API endpoint. They dynamically learn what is available and how to use it
at runtime.
MCP vs. Traditional API Integration
|
Aspect |
Traditional
API |
MCP |
|
Discovery |
Manual
documentation |
Auto-discovery
of tools |
|
Integration |
Custom code
per system |
Standardized
protocol |
|
AI
Compatibility |
Requires
wrapper logic |
Native LLM
support |
|
Operations |
Fixed
endpoints |
Dynamic tool
listing |
|
Security |
API keys /
OAuth |
Delegated
auth + config |
|
✅ Key Takeaway MCP
eliminates the need to write custom integration code for every AI client.
Once a system exposes an MCP server, any MCP-compatible agent can work with
it out of the box. |
What’s Next?
Now that you understand
agents and MCP, you are ready for Blog 2, where we dive into the Business
Central MCP Server itself, what it exposes, how to enable it, and the role of
the BcMCPProxy in connecting non-Copilot-Studio clients.
Blog Series Navigation
▶ Blog 1: Understanding AI Agents and MCP (You are here)
Blog 2: The Business
Central MCP Server
Blog 3: Building
BcMCPProxy.exe and Connecting to Claude Desktop
Blog 4: Testing
Scenarios and Best Practices
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