MCP.so
Sign In

Compliant Llm

@fiddlecube

About Compliant Llm

Build Secure and Compliant AI agents and MCP Servers. YC W23

Basic information

Category

AI & Agents

License

MIT

Runtime

python

Transports

stdio

Publisher

fiddlecube

Config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Compliant Llm?

Compliant Llm is a comprehensive toolkit for ensuring compliance and security of AI systems. It is designed for infosec, compliance, and generative AI teams to test AI agents, prompts, MCP servers, and models against internal policies and frameworks such as NIST, ISO, HIPAA, and GDPR.

How to use Compliant Llm?

Install the package via pip install compliant-llm, then launch the interactive dashboard with the command compliant-llm dashboard. Configure your chosen LLM provider and begin running security tests and compliance analysis.

Key features of Compliant Llm

  • Security testing against 8+ attack strategies
  • Compliance analysis for NIST, ISO, OWASP, GDPR
  • Supports multiple LLM providers via LiteLLM
  • Interactive visual dashboard for test results
  • End-to-end testing of AI systems
  • Detailed reports with actionable insights

Use cases of Compliant Llm

  • Ensuring an AI agent complies with internal policies and HIPAA
  • Testing an MCP server for prompt injection vulnerabilities
  • Validating LLM outputs against GDPR data privacy requirements
  • Running security audits on generative AI models before deployment

FAQ from Compliant Llm

What compliance frameworks does Compliant Llm support?

It supports NIST, ISO, OWASP, GDPR, HIPAA, and other frameworks.

Which LLM providers can I use with Compliant Llm?

It supports OpenAI, Anthropic, Gemini, Mistral, Groq, Deepseek, Azure, vLLM Ollama, Ollama, Nvidia Nim, and Meta Llama via LiteLLM.

How

Comments

More AI & Agents MCP servers