Identity and Reputation Layer for OpenClaw Agents

A developer team has built an identity and reputation layer on top of OpenClaw to address a specific problem: when AI agents chain actions in a workflow, identity information dissolves by the third step, making everything appear to come from a generic service account. This can be risky in production, especially for operations involving money movement.

The Solution: Three Components

The team's fix involved wiring identity into the execution path itself rather than adding it as configuration. Their stack consists of three main parts:

• MCP-I (Identity at execution time): Every action runs with a structured claim attached. For example: "Agent {agent_uuid} is acting on behalf of Dwayne from Accounting, with scope [user:read, subscription:write], for the purpose of reconciling our records for the month." This provides more detail than a simple "valid key" check and tracks identity through all steps of a workflow. The team built MCP-I around this model and has donated the specification to the Decentralized Identity Foundation, making it an open standard. The GitHub repository is public.
• IdentiClaw: This component addresses the identity collapse that happens in the chain of agent → tool → service → agent. Its purpose is to maintain the same identity and delegation chain throughout, providing end-to-end attribution.
• knowthat.ai: Described as a "Yelp for AI agents," this is a registry where every agent is auto-registered and interactions accumulate into a track record. It allows developers to examine behavior across multiple runs, answering questions like "Has this agent stayed within scope or has it drifted?" or "Does this agent have a record of rug pulling innocent civilians?" The team describes it as less of a logger and more of a memory layer.

The team's goal is straightforward: workflows that start with user intent should end as attributable actions, with audit logs that document what happened and who it was for. They believe this approach can help prevent agent-related issues in production environments.