Compliant LLM

v1.0.0Securitystable

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

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What is Compliant LLM?

Compliant LLM is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to build secure and compliant ai agents and mcp servers. yc w23

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

This server falls under the Security category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

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

Use Cases

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

Maintainer

LicenseMIT
Languagepython
Versionv1.0.0
UpdatedMay 21, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

Manual Installation

npx compliant-llm

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use Compliant LLM

Compliant LLM is a security and compliance platform (backed by YC W23) that lets you test and harden AI agents and MCP servers against real-world attack strategies including prompt injection, jailbreaking, and context manipulation. It evaluates your AI systems against industry frameworks such as NIST, ISO, OWASP, GDPR, and HIPAA, and supports a wide range of LLM providers via LiteLLM. Teams use it to validate agent security posture before deploying AI in regulated or sensitive environments.

Prerequisites

  • Python 3.9 or higher installed
  • pip package manager available
  • An AI provider API key (OpenAI, Anthropic, Gemini, Mistral, Groq, or others supported via LiteLLM)
  • An MCP client such as Claude Desktop or Claude Code
1

Install Compliant LLM via pip

Install the compliant-llm Python package globally using pip. This installs the CLI and dashboard tooling.

pip install compliant-llm
2

Launch the dashboard

Start the interactive Compliant LLM dashboard, which allows you to configure your LLM provider, set up test targets, and review results.

compliant-llm dashboard
3

Configure your LLM provider

Inside the dashboard, connect your AI provider (OpenAI, Anthropic, Azure, Ollama, etc.). Compliant LLM uses LiteLLM under the hood, so you provide the relevant API key for your chosen provider.

4

Run security and compliance tests

Select your target agent, MCP server, or prompt system and execute the security test suite. The platform runs 8+ attack strategies including prompt injection, jailbreaking, and context manipulation, then evaluates results against your selected compliance frameworks (NIST, ISO, OWASP, GDPR, HIPAA).

5

Review reports

After testing completes, review the generated compliance and vulnerability reports in the dashboard. Each finding includes the attack strategy used, the framework violated, and recommended mitigations.

6

Configure as an MCP server

Add Compliant LLM to your Claude Desktop or Claude Code MCP configuration so Claude can invoke security tests directly from your AI workflow.

npx compliant-llm

Compliant LLM Examples

Client configuration

Add Compliant LLM to your Claude Desktop config. The server is invoked via npx.

{
  "mcpServers": {
    "compliant-llm": {
      "command": "npx",
      "args": ["compliant-llm"]
    }
  }
}

Prompts to try

Once connected, use these prompts in Claude to trigger compliance and security analysis on your AI systems.

- "Run a prompt injection security test on my customer support agent"
- "Evaluate my MCP server against OWASP AI security guidelines"
- "Check if my AI system complies with GDPR requirements"
- "Run all 8 attack strategies against my current agent configuration"

Troubleshooting Compliant LLM

Dashboard does not start after pip install

Ensure your Python environment is active and that pip installed the package to the correct environment. Try running 'python -m compliant_llm dashboard' as an alternative, or reinstall with 'pip install --upgrade compliant-llm'.

LLM provider connection fails during testing

Verify your API key is correctly entered in the dashboard. For Anthropic, the key should begin with 'sk-ant-'. For OpenAI it begins with 'sk-'. Check that your API key has sufficient permissions and quota.

To opt out of anonymized telemetry

Set the environment variable DISABLE_COMPLIANT_LLM_TELEMETRY=true before launching the dashboard: 'export DISABLE_COMPLIANT_LLM_TELEMETRY=true && compliant-llm dashboard'.

Frequently Asked Questions about Compliant LLM

What is Compliant LLM?

Compliant LLM is a Model Context Protocol (MCP) server that build secure and compliant ai agents and mcp servers. yc w23 It connects AI assistants to external tools and data sources through a standardized interface.

How do I install Compliant LLM?

Follow the installation instructions on the Compliant LLM GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with Compliant LLM?

Compliant LLM works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is Compliant LLM free to use?

Yes, Compliant LLM is open source and available under the MIT license. You can use it freely in both personal and commercial projects.

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Quick Config Preview

{ "mcpServers": { "compliant-llm": { "command": "npx", "args": ["-y", "compliant-llm"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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