Overview
ComplyMe.AI MCP server provides legal & data protection risk analysis and audits.
Available Tools
Legal Math
The Legal Math tool is designed to provide a GDPR data protection fine analysis based on the parameters you input. Below are the specifications for the parameters you can use with this tool:
- email: (Required) Your subscription email address.
- country: (Required) The country where the third party organisation is located. Must be 2 letter ISO country code. Currently supporting 'IE' for Ireland.
- statute: (Required) The data protection legal framework to analyse the third party risk against. Currently supporting 'gdpr' for General Data Protection Regulation.
- riskdescription: (Required) A brief description of the project/incident for which the penalty risk analysis is being conducted.
- turnover: (optional) The annual global turnover of the organisation involved in the project/incident. This information may adjust the maximum penalty based on the legal framework, such as the GDPR.
- complaint_rate: (optional, default=0.01) The annual complaint rate associated with your organisation, expressed as a percentage (e.g., 0.01 for 1%). By default, it is set at 1% (0.01). This metric can help contextualise the risk based on the frequency of complaints received.
- secondary_loss_multiplier: (optional, default=0.1) The estimated secondary loss multiplier, expressed as a decimal (e.g., 0.1 for 10%). This multiplier will be used to estimate the potential secondary losses from related provisions and/or legal actions that often occur in addition to main provisions incurring penalties. By default, it is set at 0.1 (10%).
- artefacts: (optional) List of artefacts or documents in the form of URLs relevant to the analysis. URLs must start with 'https://'. Supports URLs containing Text (html, json, plain text, xml, css, javascript, csv, rtf), PDFs and Images (png, jpeg, bmp, webp). Maximum of 20 URL artefacts and 34MB per artefact.
Tool outputs:
- The applicable provisions of the specified legal framework.
- The reasoning on why the provision is applicable.
- Annualised Expected Loss - how much is expected to be lost each year.
- Potential Secondary Loss - how much is expected to be lost as a result of breaches of related provisions and/or legal actions.
Use Case
- Assess and manage the risk of a project exposed to the EU market
- Narrow down legal risks to specific provisions of the law
- Generate the value at risk (in dollars and cents) to quantify the potential costs and benefits
- Generate monetary analysis to support a business case
Personal Information Flow (PIF)
This tool is designed to generate a Personal Information Flow (PIF) analysis based on a use case description, technical information, and legal jurisdiction. The analysis includes a sequence diagram of personal information data flows and a detailed narrative description of the flow of personal information, including the types of personal information, key actors, systems, data stores and data flows, non compliance risks and areas where privacy by default principles could be applied. Below are the specifications for the parameters you can use with this tool:
- email: (Required) Your subscription email address.
- statute: (Required) The data protection legal framework to analyse the personal information risk against. Currently supporting 'gdpr' for General Data Protection Regulation, 'ccpa' for California Consumer Privacy Act, 'pipl' for Personal Information Protection Law of China.
- usecase description: (Required) A brief description of the project for which a personal information flow analysis is being conducted.
- artefacts: (optional) List of artefacts or documents in the form of URLs relevant to the analysis. URLs must start with 'https://'. Supports URLs containing Text (html, json, plain text, xml, css, javascript, csv, rtf), PDFs and Images (png, jpeg, bmp, webp). Maximum of 20 URL artefacts and 34MB per artefact.
Tool outputs:
- Detailed use case narrative.
- Non-compliance risks based on the legal jurisdiction.
- Privacy by Design recommendations.
- A sequence diagram of personal information data flows on the above.
Use Case
- Map personal information flows in complex environments
- Detect privacy non-compliance based on applicable statute
- Use Privacy By Design/Default principles to overcome privacy issues
- Use cross domain knowledge to connect the dots to solve privacy issues
FAQ
Can it be used on any client?
It can be used on any client that supports custom remote MCP Servers (on streamable HTTPS)
Where can I find more info?
For more information visit https://www.complyme.ai/blog/mcp-tutorial-specifications
服务器配置
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"args": [],
"env": {
"URL": "https://mcp.complyme.ai/mcp"
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}
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}