About Compliant LLM
Compliant LLM is an MCP server published by fiddlecube in the AI category: build Secure and Compliant AI agents and MCP Servers. YC W23.
The repository has 162 stars and 14 forks, with the last commit a year ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
git clone https://github.com/fiddlecube/compliant-llmThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
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Security checks
Static checks derived from the repository 4 hours ago. Heuristics on the source, not an audit.
- ✓README presentThe repository ships documentation.
- ✓License declaredUsable under a stated license.
- ✓Tests presentA test suite exists in the repository.
- !Dependencies pinnedNo lockfile. Installs can pull different code over time.
- !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.
1 check has not been run yet.
Releases
README
Compliant LLM is your comprehensive toolkit for ensuring compliance and security of your AI systems.
Infosec, compliance, and gen AI teams use compliant-llm to ensure that their AI agents are secure and compliant with internal policies and frameworks like NIST, ISO, HIPAA, GDPR, etc.
It supports multiple LLM providers, and can be used to test prompts, agents, MCP servers and GenAI models.
Go through our documentation for more details.
🎯 Key Features
- 🎯 Security Testing: Test against 8+ attack strategies including prompt injection, jailbreaking, and context manipulation
- 📊 Compliance Analysis: Ensure the compliance of your AI systems against NIST, ISO, OWASP, GDPR, HIPAA and other compliance frameworks
- 🤖 Provider Support: Works with multiple LLM providers via LiteLLM
- 📈 Visual Dashboard: Interactive UI for analyzing test results
- ⚡ End to End Testing: Test your AI systems end to end
- 📄 Detailed Reporting: Comprehensive reports with actionable insights
⚙️ Install and Run
# install
pip install compliant-llm
# run the dashboard
compliant-llm dashboard
Configure your LLM provider and run attacks
Support
Contact: founders@fiddlecube.ai
Meet: 🔗 Find a slot
Community: 💬 Discord, X, LinkedIn
Self-hosted or hosted cloud: Book a demo
Supported Providers
- OpenAI
- Anthropic
- Gemini
- Mistral
- Groq
- Deepseek
- Azure
- vLLM Ollama
- Ollama
- Nvidia Nim
- Meta Llama
Roadmap
- Full Application Pen Testing
- Compliant and Logged MCP Servers
- Support different Compliance Frameworks - NIST, HIPAA, GDPR, EU AI Act, etc.
- Multimodal Testing
- CI/CD
- Access Control checks
- Control Pane for different controls
- Internal audits and documentation
⭐️ Star us
🤝 Contributors
| Developers | Contributors |
|---|---|
Those who build with compliant-llm. |
Those who make compliant-llm better. |
(You have import compliant-llm somewhere in your project) |
(You create a PR to this repo) |
We welcome contributions from the community! Whether it's bug fixes, feature additions, or documentation improvements, your input is valuable.
- Fork the repository
- Create your feature branch (git checkout -b feature/AmazingFeature)
- Commit your changes (git commit -m 'Add some AmazingFeature')
- Push to the branch (git push origin feature/AmazingFeature)
- Open a Pull Request
🔒 Security & Privacy
We take data security and privacy seriously. Please refer to our Security and Privacy page for more information.
Telemetry
Compliant LLM tracks anonymized usage statistics to improve the product. No private or personally identifiable information is tracked.
You can opt-out by setting export DISABLE_COMPLIANT_LLM_TELEMETRY=true.
📝 Cite Us
@misc{compliant_llm2025, author = {FiddleCube}, title = {Compliant LLM: Build Secure AI agents and MCP Servers}, year = {2025}, howpublished = {\url{<https://github.com/fiddlecube/compliant-llm}}>, }
README fetched from the repository 4 hours ago. The original is authoritative.