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Connect Reporting Agent data to automated workflows through MCP Server

  • Updated

Who can use this feature? 

  • Available for the Enterprise package only. 

 

On this page:

About Reporting Agent data exposure to MCP Server

You can connect the Reporting Agent platform data to external workflows, analytics platforms, and AI models, to enhance flexibility and control over how you use the data. 

The feature affects data across various platform levels (organization, workspace, and digital asset). The data is exposed through the MCP server. You can access this data from the platform interface (through the Ask Level AI chatbot) or without using the platform user interface. 
 
Note: For additional details about MCP and the reporting data dictionary, visit our Level Access Developer Help Center.

How to use data tools for analysis

Our data tools provide high-level and granular data analysis capabilities. Use them to analyze overall trends in findings, drill into specific tests, and assess detailed finding-level data for root-cause analysis.

Prerequisite: You must have access to the MCP Server. For details, go to Configure the MCP server in the plafform. 

You can use the data tools in one of the following ways: 

  • Connect your Integrated Development Environment (IDE) to the Level Access MCP server, and use a copilot tool (internal AI assistant) provided by your organization. 

  • Integrate your database or Business Intelligence (BI) tools with the MCP server to retrieve reporting data directly.

  • Enter your question into the Ask Level AI chatbot for guided insights. 

Note: Accuracy and quality of answers might differ, based on the model integrated with the MCP server, for example, GPT, Claude, or Grok.

List of available data tools

The following table lists the available data tools: 

Data tool

Purpose of data tool

 Example prompts for Ask Level AI 

findings_metrics

Analyze overall trends. Access high-level findings analytics across all data levels (organization, workspace, digital asset).

Typical usage  patterns:

  • Comparing accessibility posture across organizational levels (organization vs. workspace vs. digital asset).

  • Understanding where issues, risk, or progress are concentrated within the hierarchy

  • Requests to roll up or break down metrics between levels

  • Questions that require moving from executive-level summaries to asset-level detail.

  • Comparing trends and progress within and across levels over time.

  • How many digital assets does my organization have?

  • Based on the remediation rate of all of my digital assets, which one has the lowest rate. 

  • Which workspaces have the highest number of critical issues?

  • How does accessibility progress differ between Workspace A and Workspace B?

  • Where have we seen the biggest improvements or regressions across our digital assets this quarter?

  • Which workspaces are lagging behind in remediation progress?

  • How much of our total issue count comes from a single digital asset?

test_metrics

Analyze data at the testing level, including scans and evaluations. For example, compare scan and evaluation results. 

Typical usage  patterns:

  • Comparing scans or releases. For example: "Has our score improved since September?”

  • Requests to visualize progress or time-based changes.

  • Questions about tracking accessibility Key Performance Indicators (KPIs) month over month.

  • What's changed since the last scan?

  • Can you help me with analysis of issues that scan found on <insert test URL>  ?

  • Based on the last scans from <Website A>  and <website B>, what are the main findings of each one? 

  •  What are the top five findings for the market research scan?

  • What changed since the last scan on digital asset <insert name/URL of digital asset>?

findings_details_metrics

Explore detailed, granular data at the individual finding level. Use it for root-cause analysis.

Typical usage  patterns:

  • Search and filter for specific types of findings.

  • Focus on prioritizing, filtering, and scoping issues.

  • Address issues by severity, component type, or standard (WCAG)

  • Which findings should my team prioritize?

  • Which issues should I fix from my recent manual evaluation?

  • Do we have any findings related to a Search icon issue?

  • I am looking for a Level Access finding about Update Dropdown Focus. 

  • Break down the issues (critical, high, and low).

 

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