Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Vector Decisions MCP Server Assess the deployment risk for our new autonomous agent."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP-native governance and action-assurance primitives for autonomous AI.
gatri_trust_score — legacy composite trust scoring.
assure_action — evidence-backed, context-aware assurance for one agent action.
decide_action — converts GATRI assurance + policy + permissions + context into ALLOW, RESTRICT, REQUIRE_HUMAN, or DENY.
risk_assessment — deployment risk assessment.
compliance_check — EU AI Act-oriented policy check.
kill_switch — emergency stop directive.
Related MCP server: agentguard
agent × action × context × evidence
↓
GATRI
↓
Vector Decisions
↓
ALLOW / RESTRICT /
REQUIRE_HUMAN / DENYThe important primitive is action assurance, not a generic claim that an agent is safe. The same agent can be acceptable for one action and unacceptable for another.
npm install
npm run build
npm startThe server uses stdio transport and is intended to be consumed by MCP-compatible clients.
Version 1.1.0. This is a protocol-oriented V0: deterministic local evaluation first; evidence ingestion, persistent assurance records, policy registries, signed attestations and remote APIs are subsequent layers.
Evaluate whether an AI agent has earned authority to perform one specific action in one context. Returns an evidence-derived GATRI assurance record.
Inputs: impact (required), agentId (required), purpose (required), evidence (required), +4 more.
EU AI Act compliance check. Evaluates an AI system against EU AI Act requirements.
Inputs: category (required), systemName (required), dataGovernance (required), hasTransparency (required), +4 more.
Turn GATRI assurance plus policy/context into an operational Vector Decision: ALLOW, RESTRICT, REQUIRE_HUMAN, or DENY.
Inputs: impact (required), sensitivity (required), policyPassed (required), assuranceScore (required), +6 more.
Compute GATRI trust score for an AI agent. Evaluates Governance, Accountability, Transparency, Robustness, and Inclusivity.
Inputs: agentName (required), governance (required), robustness (required), inclusivity (required), +2 more.
Emergency halt for an AI agent. Issues a kill-switch directive to immediately stop agent operations.
Inputs: reason (required), severity (required), agentName (required), scope.
Comprehensive risk assessment for an AI agent deployment.
Inputs: agentName (required), ethicalRisk (required), securityRisk (required), complianceRisk (required), +2 more.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Scored across 6 tools
Each tool targets a distinct concern: trust scoring, emergency halt, compliance, risk assessment, action assurance, and decision-making. While trust and risk are related, they are conceptually different (governance quality vs. deployment risk), and the assurance/decision pair forms a clear pipeline without overlap.
All tool names follow a consistent snake_case pattern with clear verb/noun structure (e.g., kill_switch, compliance_check, decide_action). The use of the 'gatri' prefix in gatri_trust_score is a minor deviation but doesn't break the consistency.
Six tools is well within the ideal range and maps cleanly to the server's governance/decision-making domain. Each tool adds unique capability without redundancy, and the count feels appropriately scoped.
The tool surface covers the core lifecycle: assessment (trust, risk, compliance), action-level assurance, decision output, and emergency control. Minor gaps exist, such as policy management or audit trail retrieval, but these are not essential to the primary workflow and can be worked around.
Pre-execution governance for AI agents. Deterministic PASS/FAIL/REVIEW verdicts, replayable proof.
Pre-deploy governance for AI agents: posture scores, policies, budget cap checks, trust manifests.
Zero-trust gateway for AI agents: score tool calls, verify agent cards, enforce policy, audit.
Register every AI agent, log every action, prove it. EU AI Act compliance built in.
