With MCP, Microsoft established a standard that enables AI agents to access data and business logic across Dynamics 365 Finance, Supply Chain Management, HR, and Project Operations in a controlled manner. The MCP server acts as a “standard connector” for developing AI agents that support existing processes – from finance and procurement through to production. In the following sections, we will present specific MCP Dynamics 365 use cases -showing how MCP can be used in a very practical way in your day-to-day ERP work.
What Microsoft already provides today: standard agents in Dynamics 365
Microsoft already provides several standard agents for Dynamics 365 – for example, for account reconciliation, supplier communication, time and expense recording, approvals, or resource scheduling. These preconfigured agents must be explicitly activated in the Finance and Operations apps and demonstrate which tasks are well-suited for AI agents. You can find a more detailed classification of the standard agents in our introductory article What is the Model Context Protocol (MCP)?
01
Data quality and master data: from missing e-mail addresses to new legal entities
A classic introduction to the topic of AI agents is data quality. For example, a data quality agent can check whether all supplier data is complete and report specific deviations, such as when no valid email address is stored for a supplier. This allows gaps to be closed systematically without teams having to check lists manually.
Beyond that, MCP is suitable for converting unstructured information into structured Dynamics 365 data, making duplicates visible, and keeping master data more consistent. On this basis, further scenarios can be built, such as better planning and scheduling suggestions that take delivery performance into account.
The semi-automated configuration of new legal entities is also particularly powerful. An AI agent can create a new legal entity based on an existing client and adopt central settings, customer, and supplier parameters. This saves time during rollouts, but also requires clear approvals before the new client goes live.
02
Procurement and supply chain: suppliers, purchase orders, conditions
In procurement, several scenarios can be represented via MCP. Even in the early, static MCP version, Microsoft provided tools to find approved suppliers, check stocks, create orders, or transfer non-matching invoices to workflows. The dynamic MCP server continues this approach and opens it up to custom, process-specific actions.
For example, an agent can help create new suppliers: it automatically sends emails requesting missing information, such as bank details, addresses, or certificates, and then transfers the verified responses into the system in a structured way. When placing an order, it can also check which supplier currently makes the most sense for an item – for example, based on price, delivery time, and stock levels – thereby taking over what was previously manual research in the system.
In dunning processes, an agent can work across clients: it looks at items due across multiple legal entities, prepares dunning runs, and displays exceptions. MCP is particularly interesting for international groups because it makes relationships visible that would otherwise remain hidden within individual clients.
03
Finance: reconciliation, outliers, and cash flow
In the finance area, there is a first-party agent from Microsoft, which is expected to be migrated to MCP in the future. The account reconciliation agent reconciles subledgers with the general ledger. For example, it highlights postings that exist only in the subledger or only in the general ledger, and enables direct navigation to the affected postings or the preparation of corrections.
Another suitable scenario is detecting data outliers. An AI agent monitors defined G/L accounts and automatically reports when postings deviate noticeably from the typical monthly values. This makes irregularities visible without having to review all reports every month manually.
MCP can also support cash flow analysis by evaluating customer payment behavior not only based on due dates, but also by actual payment history. This results in more realistic liquidity forecasts that account for historical patterns.
04
HR and employee lifecycle: preboarding, onboarding, self-service
Preboarding and onboarding agents in the HR environment are particularly illustrative. An agent can review employee data, automatically send emails containing data stored in the system (bank details, address, certificates), and request confirmation or correction. A second agent reads the answers, prepares structured change proposals, and asks an HR person whether these adjustments should be applied. This pattern – outbound agent, inbound agent, human-in-the-loop – ensures efficiency without handing over full control to the AI.
Building on this, onboarding tasks can also be automated: an agent can use roles in D365 to fill onboarding checklists and distribute tasks to the right people via Microsoft Teams.
05
Sales and service: sales orders and documents from unstructured data
A typical example in sales is the sales order agent: it reads incoming order emails, interprets their content, and, if everything is plausible, automatically creates a sales order in Dynamics 365. The department teams only have to review and approve the order, rather than manually entering each one.
Another scenario comes from the automotive sector: a car dealership takes a used vehicle as a trade-in. Instead of manually writing the sales description, an agent can evaluate a photo and additional details, recognize the relevant data, and generate an initial draft of a sales document or advertisement. This turns unstructured information into clean, reusable texts.
06
Warehouse, quality, and operations: inventory, quality orders, and batch monitoring
- In warehouse and quality management, a Dynamics 365 MCP agent can monitor inventory levels and automatically suggest new purchase orders if an item falls below a defined threshold. Quality orders can be created or reinforced for quality processes if the agent recognizes anomalies and suggests additional inspections.
- For technical operations, a batch monitoring agent is a good fit. Instead of manually checking every morning whether all batch jobs have run successfully, this agent monitors batch processing and reports errors or delays, including links to the affected processes. This allows business teams and IT to focus on the real problems.
07
Internal management and continuous improvement
MCP is also suitable for tasks beyond day-to-day operations. One example of this is test automation agents that execute and document recurring test scenarios in the ERP system. Process mining scenarios can also be set up in which an agent analyzes process flows, highlights deviations, and identifies bottlenecks, thereby creating the basis for subsequent automations.
A very tangible use case is the time entry agent in combination with Dynamics 365 Project Operations. This agent reviews calendars and emails, matches this information with the projects to which times can be booked, and suggests suitable time entry records. When booking their times, employees no longer have to start from scratch, but can review, adjust, and approve the AI-generated suggestions. This saves time and reduces errors, especially in companies with a high volume of time bookings.
08
Language, clients, analytics: comprehensive scenarios
MCP can also help to reduce language barriers. An agent understands multiple languages, reads German documents, for example, and provides Danish colleagues with answers in Danish – without the intermediate step of manual translation.
There is also the option of working across multiple clients. An agent can view consolidated data from several legal entities – for example, for dunning, management reporting, or group-wide analyses. In combination with an MCP server for business performance analytics, this creates an end-to-end overview from operational data to analytical views.
Agentic Readiness Check
Are you ready to use AI agents? In our free agentic readiness check, you can find out whether your company meets the technical and organizational requirements for using agentic AI.
- A fast, well-founded analysis of your status quo.
- Individual assessment: where do AI agents really make sense for you?
- Concrete roadmap from quick wins to long-term measures.
Conclusion: MCP is a key building block for agents in Dynamics 365
With MCP, Microsoft is standardizing the bridge between AI agents and ERP systems. The Dynamics 365 ERP MCP server and complementary MCP approaches for analytics provide agents with controlled access to data and business logic via a protocol which is gaining traction in the industry. When used correctly, this results in a tangible relief: fewer clicks, fewer media disruptions, more time for business decisions. However, use cases, security, and governance must be taken into account from the very start. Feel free to get in touch with us!
