Here you’ll find a suite of experiments and tools, some just getting started, some ready to test, all open to feedback and community input. Each project is presented as a flask, representing different stages of experimental development. Learn more about flask status →. Flasks are standalone services, libraries or tools, that can be used independently or together to build more complex applications. Explore the flasks below or get in touch if you want to contribute, try things early, or shape what comes next.

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🚀 Getting Started

Want to try out these experiments? Get started here.

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💬 Feedback & Contribution

We’re building in the open and love community input. Learn how to contribute.

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🧪 Flasks

Our current experiments focus on Model Context Protocol (MCP) tools and AI security. These tools help developers build safer, more controlled AI applications with proper identity and authorization.

MCP Hub

A hosted MCP Manager unifying and orchstrating multiple MCP servers, focusing on auth and security

Guardrail Proxy

Wrap any MCP server in a configurable and flexible security layer

Bodyguard

LLM-based threat detection for prompts and tool calls

Pass-through Proxy

Middleware hook system for MCP servers that powers guardrails and more

Civic Knowledge

AI assistant for the optimisation of internal operations and processes

MCP Hub Components

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📚 Concepts & Architecture

Understanding the building blocks behind our experiments.

Model Context Protocol

What is MCP and why it matters for AI applications

Guardrails

Guardrails as a protection layer

Prompt Injection

Understanding prompt injection attacks & LLM safety

Auth Strategies

OAuth2, granular permissions, and consent

Hooks

A middleware layer around MCP APIs

RAG

Retrieval strategies for LLMs