MCP for Quality of Earnings Support: Reconciliation and Review

The Model Context Protocol (MCP) provides a secure way for AI assistants to access live data from a client's business systems, streamlining the laborious process of preparing a Quality of Earnings (QoE) report. For sell-side M&A advisors, this means faster reconciliation, easier evidence gathering for adjustments, and more time spent on high-value analysis rather than manual data extraction. MCP acts as a controlled gateway to the data, ensuring the AI only sees what it's permitted to see.

The problem: Manual reconciliation in QoE analysis

Preparing a sell-side QoE report is a critical but often grueling task. The process is dominated by manual, time-consuming activities that introduce risk and slow down the deal timeline. Advisors spend countless hours:

• Extracting data: Pulling trial balances, general ledger details, and transaction-level reports from unfamiliar client ERP and accounting systems.
• Ticking and tying: Manually cross-referencing numbers between financial statements, GL entries, and source documents stored in a virtual data room (VDR).
• Managing spreadsheets: Juggling multiple Excel files for different analyses, creating a high risk of version control errors, broken formulas, and data inconsistencies.
• Tracing adjustments: Laboriously hunting for evidence to support every normalization adjustment, from a one-time legal expense to non-recurring revenue.

This manual workflow is not only inefficient but also prone to human error. A single copy-paste mistake or incorrect filter can lead to inaccurate conclusions, damaging credibility with potential buyers.

Illustrative example: Tracing revenue adjustments with MCP

Imagine an M&A advisor preparing a QoE for a client that uses NetSuite and an Intralinks VDR. The advisor needs to identify and exclude non-recurring revenue from a one-off consulting project to normalize EBITDA.

Without MCP: The advisor would request a GL dump from the client, filter it in Excel, and then manually search the VDR for the specific contract and statement of work to confirm the project's non-recurring nature. This could take hours.

With MCP: The advisor uses an AI assistant (like Claude) connected via an MCP server to both the client's NetSuite instance and the VDR. They can simply ask a natural language question:

The AI, through the MCP server, queries NetSuite for the transaction data and searches the VDR for the corresponding documents. It returns a concise summary with direct links to the evidence. The advisor can verify the adjustment in minutes, with a clear, auditable trail from the QoE report back to the source data. This workflow transforms QoE support from a manual search exercise into a rapid, evidence-based review process.

A quality of earnings reconciliation worksheet

Using an MCP-enabled AI assistant does not replace the need for professional judgment in a QoE analysis. Rather, it supercharges the analyst's ability to gather and verify the necessary data. This worksheet provides a template of prompts that an M&A advisor could use to accelerate their reconciliation work.

Prerequisites and limitations

Successfully using MCP for QoE support requires a specific technical and operational setup.

• Authorized Access: The client company must explicitly authorize access to its systems (e.g., ERP, CRM, VDR) for the specific purpose of the QoE engagement.
• MCP Connectors: The client's software must be supported by an MCP connector. While many modern systems like NetSuite, QuickBooks, Salesforce, and Intralinks have developing support, legacy or custom-built systems may require custom integration work.
• Professional Judgment: MCP is a powerful data retrieval tool, not an accounting expert. It accelerates the 'what' and 'where', but the 'why'—the materiality of adjustments and the final opinion—still requires an experienced M&A or accounting professional.
• Data Quality: The output from the AI is only as good as the underlying data. Inconsistent data entry, poor categorization, or missing records in the client's systems will limit the effectiveness of MCP-powered analysis.
• Separate Licensing Rights: Using MCP to review client data for a QoE engagement does not grant your firm or anyone else the right to license that data for other purposes, such as training AI models. Data licensing is a completely separate process that requires explicit, informed consent from the company. Read more about this distinction in our guide on MCP and data licensing rights.

Questions to ask your software provider or implementation team

1. Which specific versions of ERPs like NetSuite, QuickBooks, and Dynamics 365 does your MCP server support?
2. How does the MCP server integrate with virtual data rooms to link financial data to source documents? Can you describe the workflow with Intralinks or DealCentre? See more on MCP and virtual data rooms.
3. What is the process for distinguishing between a company's internal records and third-party licensed research (e.g., PitchBook, AlphaSense) to prevent data contamination or misuse? Learn about keeping sources separate.
4. What MCP audit logs are maintained to create a verifiable record of every query performed against client data during a diligence engagement?
5. How are user permissions and access controls configured on a per-client, per-engagement basis to ensure strict data segregation and confidentiality?

Next step with SourceX

As you guide clients through the sale process, you develop a deep understanding of their operations and the data that underpins their value. This unique vantage point allows you to spot opportunities beyond the immediate transaction. One such opportunity is data licensing.

SourceX manages the supply and transaction layer for enterprise AI data, connecting companies with valuable, non-public data to AI labs and data buyers. This creates a new, non-dilutive revenue source for the operating company. The process is always permission-based and managed separately from any M&A or advisory work.

If you have clients that might be a fit—typically US-based companies with over 50 employees and robust operational data—you can introduce them to SourceX. For each permissioned introduction that results in a data-licensing transaction, our partners receive 25% of the platform fees SourceX collects, up to $100,000 per referred company. This reward is a share of SourceX's fee, not the company's own proceeds from the license. To start, you can screen a few permissioned clients using our free, confidential Portfolio Data Opportunity Scanner or learn more about our partner program.

Related MCP guides

• MCP for M&A Due Diligence: Connecting AI to Live Deal Data
• MCP and Virtual Data Rooms: A Guide for Secure AI-Powered Due Diligence
• MCP and Data-Asset Due Diligence: A Guide for Sell-Side M&A Advisors
• NetSuite MCP Server: A Guide for CFO Advisory Firms
• All MCP resources

Sources

• Anthropic finance agents (May 5 2026)
• Intralinks confidential deal data (Current guide)
• AlphaSense MCP overview (Current beta docs)
• PitchBook data in Claude (October 28 2025)

Vendor capabilities change. Check current official documentation before relying on any product detail.