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Govern agent decisions with auditable evidence, confidence calibration, and policy-based handoffs.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "governed-mcp" yet — see the docs or source repo.
Use governed-mcp to check whether this agent decision complies with governance policy, and return an auditable evidence record, confidence notes, and whether a human handoff is needed.
A policy-based decision review with evidence records, confidence calibration details, and a handoff recommendation.
Use governed-mcp to assess the confidence of the current agent conclusion, and based on governance policy say whether it should proceed, request more evidence, or hand off.
A confidence assessment with policy-guided guidance to proceed, gather more evidence, or hand off.
Use governed-mcp to generate an auditable evidence record for this agent decision and summarize which policies or evidence supported each step.
A structured evidence trail for auditing, review, and accountability.
Developers or product managers can use it to enforce policy on critical decisions made by autonomous agents and retain auditable evidence. This helps reduce the risk of unsafe decisions being executed directly.
When an agent's conclusion is not confident enough, teams can use it to calibrate confidence and decide, based on policy, whether to hand off to a human or another process. It fits automation flows that require explicit handoff rules.
For retrospectives or compliance review, teams can use it to inspect the evidence records and governance basis behind agent decisions. This makes it easier to trace why a particular decision was made.
It is an MCP server that applies governance controls to agent decisions. It focuses on auditable evidence records, confidence calibration, and policy-based handoff guidance.
It is suited to scenarios where autonomous agent decisions need constraints, helping teams understand decision rationale, calibrate confidence, and perform handoffs under policy. It is especially useful for workflows that require auditing and accountability.
The provided information does not include installation steps, runtime details, or key requirements. For prerequisites, see the source repository.
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