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Pseudonymize PII before LLM calls and get signed receipts for responses.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "io.github.Declade/lucairn-mcp-server" MCP server from askskill: Run: claude mcp add 'io-github-declade-lucairn-mcp-server' -- npx -y @lucairn/mcp-server
Developers or DevOps teams can pseudonymize personally identifiable information before sending business text to an LLM, reducing direct exposure of sensitive data. Each response also includes a signed receipt for traceability.
Researchers analyzing interviews, feedback, or tickets can pseudonymize names and contact details before sending the text to an LLM. This preserves analytical value while reducing exposure of raw identity data.
When teams need verifiable proof of model responses, this tool returns a cryptographically signed receipt for each response. It fits AI workflows that emphasize compliance and traceability.
It pseudonymizes PII before content is sent to an LLM and returns a cryptographically signed receipt for each response. It is suited for LLM workflows that need privacy protection and response traceability.
Based on the description, the receipt is cryptographically signed and can serve as proof or a trace record for each response. For exact verification methods and format, see the source repository.
The provided material does not include installation steps, runtime details, or key requirements. For prerequisites and deployment instructions, see the source repository.
Proxy internal APIs for Claude while automatically masking sensitive banking data.
Securely let LLMs query synthetic clinical data with scoped access controls.
Secure MCP server enabling OAuth 2.1 and PKCE for remote LLM connections
Pseudonymize and restore patient PII locally for HIPAA-safe workflows.
Automatically generate signed tamper-evident receipts for compliant, traceable tool calls.
Delegate low-risk tasks to a cheaper model with main-agent review.