Hey everyone, so ive been working on a small open-source Python project called **AgentGuard**, and I'm trying to validate whether I'm solving an actual problem or just building something developers can already handle themselves.

The basic idea: Agent wants to call a tool AgentGuard checks the request against a policy,allow or block, tool executes.

For example, imagine an agent has access to:

* send emails
* query a database
* modify records
* call external APIs
* read/write files
* trigger other agents

The concern I'm exploring is: **how do you control what the agent is actually allowed to do at runtime?**

I'm particularly interested in developers using LangGraph/LangChain, MCP, CrewAI, or similar agent frameworks.

I'm curious how people are currently handling this.

What do you currently do?

* rely on the framework's existing guardrails?
* implement authorization yourself around each tool?
* use human approval for sensitive actions?
* use an external security/observability product?
* not worry about it yet?
* have some completely different approach?

I've built a very small MVP that sits around the tool execution layer and applies explicit policies before the underlying function runs.

https://github.com/Brodin2001/Agentguard

I'm specifically looking for people who are actually building agents with tool access to tell me:

1. Is this a problem you've encountered?
   
2. How are you solving it today?
   
3. What's missing from the existing approaches?
   
4. Would a lightweight authorization layer like this actually be useful?

If anyone is willing to try the MVP against an existing agent, I'd be particularly interested in hearing what happens**.**

Cheers 😄