This is a complex task, and I want to avoid blatant self-promotion, but there are solutions that people are building which allows you to give a degree of freedom to your agents but also lock them down as well. Our company has a product which is just one such example. At this point it's really geared towards orgs running agents in a cluster to handle tasks, rather than e.g. making sure your claude code doesn't post your GPG keys to the blockchain or something.
In essence, you lock down all the agents completely except for permitted use cases; X agent can talk to Y agent, Z agent can talk to Q MCP server.
You register your agents, define things around them, what they can and can't do, which LLMs they can actually talk to, what sites they can access, network controls, etc.
We call ours Lynx, and it's a pretty cool product. As I said, this isn't for people running coding agents or openclaw or whatever, though the technology could do that if you coupled it with e.g. some kind of MicroVM sandbox like docker's sbx. If you want to see the sort of controls that you can put on an agent we have demo videos and stuff that show how things work: https://www.tigera.io/tigera-products/lynx/
The idea for Lynx is:
1. Your org has a bunch of scoped agents
2. You have a fixed list of what those agents should be doing and what they need to be accessing
3. They don't or won't need to access anything else
So for example, say you have an MCP server which gives you information about a kubernetes cluster. You create an agent that can query that MCP server and summarize information about it. You also have a database that associates kubernetes namespaces with the departments that use them, and an MCP server for that.
Now you can create an agent whose sole purpose is to generate usage analysis for the kubernetes cluster broken down by department.
Then maybe you have another agent with access to an MCP server which shows cloud spend in detail. That agent can query the first agent to get usage analysis and then cross-reference it with cloud spend to determine if any departments are showing sudden cost increases and generate a report for that.
The first agent gets locked down to only access those two MCP servers and whatever LLM. The second AI gets locked down to only access the first agent, the cloud MCP server, and whatever LLM.
The whole system is really neat. I think for a more open agent, like openclaw for example, you'd probably want to build out that sandbox with its own interactive permissions management; sort of like Little Snitch on macOS, where it pops up something asking if you're okay with program X doing network connection Y, you could have the sandbox say "agent is trying to access docs.foobar.io, is that okay?" or "agent is trying to run `gh pr list`, allow?" It's not realistic to pre-specify everything that Claude Code is allowed to do or access; even "raw.githubusercontent.com" could be the README for the program you're debugging or someone's sandbox-escaping exploit, but it's a good start.