MCP Governance is a design partner program. It is not generally available. Ask your Lumos account team or email leo@lumos.com to join.
What you see on day one
After you turn on MCP Governance, Lumos shows tool calls as people work.- Every MCP server in use. A server appears the first time someone calls it, including servers no admin approved. Locally added servers live in configuration files on the employee’s machine, so no vendor API can enumerate them. Watching the calls is the only way to see them.
- Not only MCP. The hook sees every tool the agent runs, so shell commands and file edits are captured alongside MCP calls.
- A searchable call history. Narrow to one person’s week, one server, or one tool, and chart the volume over time. You can answer “who has been calling this, and how often” without a log export.
What you control
Set policies that allow or block tool calls before they execute.- Allow or deny, per tool. A policy matches on the MCP server, the tool name, whether the tool reads or writes, the person’s email, or the arguments of the call. A server can be open for reads and closed for writes.
- One click for the common case. Open a server and select “Allow reads” or “Block writes”. Lumos writes the policy for you, scoped to that server.
- Policies are ordered, and the first match wins. Place a policy where you want it to apply. A block belongs above the allows it is meant to override.
- The default is Allow. Nothing blocks until a policy says so. When your policies are in place, set the domain default to Block.
- A blocked call names the policy that stopped it. The person sees the policy name in the agent transcript they are already reading.
Ask Albus
Albus, the Lumos AI assistant, reads your call history and helps you build policies.- Discover tool call patterns. Ask which servers your teams actually use, who called a tool last week, or what a spike came from. Albus reads the call history and answers, so you don’t need to search through logs.
- Build policies in plain language. Describe the rule you want and Albus writes it. Albus uses the servers and tools it already sees in your organization, so the conditions fit your environment rather than a template. It edits and reorders existing policies too. Every change comes back as an approval card before it takes effect.
What Lumos stores
For general security questions, see trust.lumos.com.
Supported agents and clients
Getting started
Lumos installs a hook that runs in the agent before each tool call and returns allow or deny. To see how it works, read How hooks work. To roll it out across your fleet, follow the MCP Governance rollout guide.1
Lumos turns MCP Governance on for your domain
Ask your Lumos account team or email leo@lumos.com. This is a design partner program, so Lumos enables it per domain.
2
Initial users install the hook
Each user runs one command from app.lumosidentity.com/mcp/install. Usage is unaffected until a policy says otherwise.
3
Open MCP Governance in Lumos
Go to app.lumosidentity.com/mcp_tool_usage to view tool calls, then set policies.
Frequently asked questions
Can you support Claude Desktop and Claude.ai?
Can you support Claude Desktop and Claude.ai?
Lumos supports Claude Code inside the Desktop app. Claude Cowork support is coming soon. Claude.ai chat is not supported because it does not expose the tool-hook interface.
Can we view and govern custom MCP servers?
Can we view and govern custom MCP servers?
Yes. Lumos sees and controls every MCP server, including custom and locally added ones, as well as every other tool call made in an agent session.
What performance impact does Lumos add to tool calls?
What performance impact does Lumos add to tool calls?
Lumos runs a policy check before each tool call and targets under 50 milliseconds per check. Agent workflows typically run for many seconds and make multiple tool calls, so the overhead does not affect the user experience.
Does Lumos see prompts or model output?
Does Lumos see prompts or model output?
No. Lumos evaluates and stores the server, tool, caller, time, verdict, and (optionally) tool call arguments. It never sees user prompts or model responses.