AgentOps Security

Your AI agents are running shell commands, editing code, opening PRs with zero local guardrails. That is insane. We just dropped a full open source local-first #AgentStack for orchestration. One CLI for scanning, firewall policy, sandboxing, cost checks, review. Works standalone or as a full kit. This is the layer nobody is building and everybody needs. Agents without local guardrails will blow up on you. It's not a question of if. Works with Codex, Claude, Gemini, OpenCode, Cursor, MCP-heavy repos. All outputs stay in local repo files. No hosted service. This is how it should work. The orchestra layer is the actual #AgentOps bottleneck right now. If you're running agents without this you're flying blind. github.com/AgentOpsSec/st…

If you're running scattered agent security tools with no shared context right now, take a look.

The #AIAgentOps security stack should work the same way. Local-first. Composable. No coupling. No SaaS middleman where one isn't needed. We're building toward this at agentopssec.com/stack

Your agent stack isn't insecure because you're missing a tool. It's insecure because your tools don't talk to each other. This is the real #AgentSecurity gap right now and almost nobody is addressing it.

If you're ignoring #AIAgentRisk by wiring MCP servers into production without auditing permissions, you're one bad tool away from a real incident. Check it out: agentopssec.com/mcp-doctor What does your MCP audit process look like right now?

4. Log every tool call. Make it replayable. 5. Review the surface before you run. This is exactly what we built MCP Doctor to solve. Scan before trust. Policy before access. Logs before assumptions.

Most devs plugging MCP servers into their agents right now have zero idea what permissions those tools actually have. Filesystem access. Shell execution. Network calls. All invisible by default. This is a #MCPSecurity blind spot begging to be exploited. Let me break it down.

Not a SaaS dashboard. Not a compliance checkbox. A real control point with actual #AgentGuardrails baked in. We built this. It's open source. agentopssec.com/mcp-firewall If you're running agents in production with MCP servers and no control layer, you're flying blind.

The missing layer is a local proxy between the agent and the tool - a real #LLMSecurity firewall for MCP tool calls. Policy-as-code for AI agents. Runs on your machine. Keeps data local. Gives you visibility into exactly what the agent is doing before it does it.

You wouldn't give a contractor root access to prod. So why are you giving it to your AI agent? Right now MCP servers are handing agents shell access, filesystem access, database queries, and API calls with zero control layer in between. Nobody is talking about this. Thread.