agentic-radar
by splx-ai · Python · Apache-2.0
A security scanner for your LLM agentic workflows
Overview
A security scanner for your LLM agentic workflows
agentic-radar is a credible open-source option worth evaluating, maintained by splx-ai with 985 GitHub stars. It targets the Integration layer of the agent stack — where reusable skills, MCP servers, and tool integrations accelerate production workflows.
Tagged with agentic-ai, agentic-framework, agentic-workflow, ai, ai-red-teaming, ai-security, and more, this skill fits naturally into modern agent architectures that combine LLMs, tools, and memory.
Key Features
- Pre-built connectors for popular SaaS and developer tools
- Webhook and event-driven triggers for agent workflows
- OAuth and API key management patterns
- Bidirectional sync between agents and external systems
- Error handling and retry logic for flaky third-party APIs
- Documentation and examples for common integration paths
Use Cases
- Sync CRM updates from sales conversation summaries
- Create Jira tickets from support agent escalations
- Post Slack digests from nightly research agent runs
- Bridge Notion wikis into RAG knowledge bases
Integration
Primary integration surface: Agent frameworks (LangChain, LangGraph, CrewAI, custom loops).
Implementation language: Python — check the repo for package install instructions.
Official homepage: https://splx.ai
Most skills support environment variables for API keys and configurable endpoints.
For MCP servers, add the server config to your client JSON and restart the host application.
Who It's For
Developers building integration-heavy agent features who want open-source building blocks.
Teams standardizing on MCP or shared tool libraries across multiple agent products.
Indie hackers and startups optimizing time-to-ship for agent MVPs.
Technical evaluators comparing alternatives before committing to a stack.
Getting Started
- Clone or install from https://github.com/splx-ai/agentic-radar.
- Read the README for prerequisites (Node, Python, Docker, API keys).
- Import the package into your agent framework and register tools.
- Run the provided example or quickstart script to verify connectivity.
- Iterate on prompts and tool schemas using the project's test utilities.
- Pin versions in production and monitor upstream releases for breaking changes.
Community & Trust Signals
985 GitHub stars indicate growing community interest.
License: Apache-2.0. Verify compatibility with your product's distribution model.
Last repository activity: November 2025.
Review open issues and PR velocity to gauge maintainer responsiveness.
Star and watch the repo to track releases and security advisories.
Topics
Strengths
- Strong fit for integration workflows in agent applications
- Open source with transparent codebase for security review
- Apache-2.0 licensed
- Well-categorized (agentic-ai, agentic-framework, agentic-workflow)
Considerations
- Verify API costs and rate limits when connecting to paid LLM providers
- Test in a sandbox before granting production credentials or network access
- Upstream breaking changes may require periodic upgrades
- Align data handling with your privacy and compliance requirements