GIA Governance

AI workforce governance control plane.

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What it can do

  • Classify Decision: Classify an AI agent decision using the MAI Framework (Mandatory/Advisory/Informational). Returns classification level, confidence score, gate requirements, and rationale.
  • Evaluate Threshold: Compute the Storey Threshold — escalation rate (gates required / total operations). Returns current rate, status, and recommendations. Healthy band 10-18% is a design heuristic, no
  • Score Governance: Compute weighted governance score from caller-provided Integrity, Accuracy, and Compliance values (0-1). Returns weighted composite and pass/fail against configured thresholds. Score

What data it sees

Do you need an account

No: the server works without sign-in

AI workforce governance control plane. 29 governed MCP tools for decision classification (MAI framework), compliance scoring, audit chain verification, risk assessment, and multi-vendor AI governance. Built for enterprise AI compliance including NIST 800-53, CMMC 2.0, EU AI Act, and SOC 2. Every AI action is classified, audited, and governed through one contract.

How to connect

How to connect GIA Governance to Claude

The server address to paste into Claude settings:

https://gia-governance--knowledgepa3.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect GIA Governance to ChatGPT

The server address to paste into ChatGPT settings:

https://gia-governance--knowledgepa3.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect GIA Governance to Cursor

The server address to paste into Cursor settings:

https://gia-governance--knowledgepa3.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (29)

Raw names from tools/list. Only developers need these.

classify_decisionClassify an AI agent decision using the MAI Framework (Mandatory/Advisory/Informational). Returns classification level, confidence score, gate requirements, and rationale.
evaluate_thresholdCompute the Storey Threshold — escalation rate (gates required / total operations). Returns current rate, status, and recommendations. Healthy band 10-18% is a design heuristic, not empirically validated.
score_governanceCompute weighted governance score from caller-provided Integrity, Accuracy, and Compliance values (0-1). Returns weighted composite and pass/fail against configured thresholds. Scores are caller-assessed — this tool applies weights and thresholds, not independent evaluation.
audit_pipelineQuery the audit ledger for governance entries. Search by operation name or retrieve recent entries. Returns hash-chained audit trail with MAI classification context.
monitor_agentsMonitor the status and health of all governed AI agents. Returns supervisor state, repair history, and failure counts.
map_complianceMap GIA governance components to regulatory compliance frameworks (NIST AI RMF, EU AI Act, ISO 42001, NIST 800-53, LINDDUN, MITRE ATLAS). Shows which controls are implemented.
assess_risk_tierAssess the risk tier of an AI system using rule-based mapping to EU AI Act categories (Unacceptable, High, Limited, Minimal). Returns tier and MAI governance recommendations. Classification is heuristic, not a legal determination.
generate_reportGenerate a governance status report. Includes system health, threshold status, compliance coverage, and operational metrics.
system_statusGet full GIA system status including engine health, uptime, governance metrics, and configuration.
approve_gateApprove or reject a pending MANDATORY gate decision. Lists pending gates if no gate_id provided. This is the human-in-the-loop mechanism for MANDATORY classifications.
seal_memory_packCreate and hash-seal a new Governed Memory Pack (GMP). The pack becomes an immutable, TTL-bound institutional knowledge artifact with trust level enforcement.
load_memory_packLoad a Governed Memory Pack into agent context. Validates TTL, trust level, role access, context class, and hash integrity before loading.
transfer_memory_packTransfer a memory pack between agents via a governed knowledge corridor. Creates a derived pack with transfer provenance. ALWAYS requires MANDATORY gate — no silent transfers.
compose_memory_packsCompose multiple memory packs into a unified execution context. Highest risk level wins, shortest TTL wins, roles intersect, trust level contaminates downward.
distill_memory_packDistill governance patterns from usage history into a draft heuristic pack. Returns EPHEMERAL draft that requires MANDATORY gate to approve for production use.
promote_memory_packPromote a memory pack to a higher trust level after human review. This is how distilled EPHEMERAL packs become CASE or ORG packs. Requires MANDATORY gate.
record_value_metricRecord a workflow value metric — tracks time saved, risk blocked, success rate, autonomy level, and task complexity for ROI reporting.
record_governance_eventRecord a governance event — tracks gates triggered, drift prevented, violations blocked, red team findings, and human interventions for impact reporting.
generate_impact_reportGenerate a full economic + governance impact report. Returns pilot ROI data: time saved, cost avoided, risks blocked, success rate, autonomy trend, and confidence levels.
srt_run_watchdogRun real health check probes from the MCP container (API health, frontend, disk, memory, TLS cert, DB, DNS). Returns actual measured values — never uses AI-provided data. Classification: INFORMATIONAL — read-only, no side effects.
srt_diagnoseRun the SRT Diagnostician on an incident. Matches finding to known playbooks, identifies root cause, and proposes a staged repair plan. Classification: ADVISORY — read-only analysis, no mutations.
srt_approve_repairApprove or reject a pending SRT repair plan. Classification: MANDATORY — this is the human-in-the-loop gate. Repair plans CANNOT execute without explicit human approval. Pass action="approve" to approve or action="reject" to reject.
srt_generate_postmortemGenerate a structured postmortem report for a completed SRT incident. Includes timeline, root cause, what worked/failed, prevention actions, metrics (TTD/TTDiag/TTR), and optional playbook delta. Classification: ADVISORY.
verify_ledgerVerify the integrity of the hash-chained forensic audit ledger. Recomputes every SHA-256 hash from genesis and reports whether the chain is intact. Classification: INFORMATIONAL — read-only, no side effects.
gia_scan_environmentRun scout swarm to detect target environment — OS, containers, services, network, storage. Returns EnvironmentProfile for compatibility checking. Classification: INFORMATIONAL — read-only, no mutations. Scout outputs are redacted for sensitive content.
gia_list_packsList available governed operations packs. Filter by intent (remediation/patrol/hardening/audit), category, risk level, or trust level. Classification: INFORMATIONAL.
gia_dry_run_packPreview remediation pack execution — shows hydrated commands, compatibility check, validation, blast radius. Returns inputsHash for approval binding (what-you-approved-is-what-ran). Classification: ADVISORY — read-only preview, no execution.
gia_apply_packExecute a remediation or hardening pack with MANDATORY gate approval. Requires inputsHash from gia_dry_run_pack (what-you-approved-is-what-ran binding). REJECTS patrol/audit packs (use gia_run_patrol for those). Hardening packs run preflight checks before execution. Classification: MANDATORY — human approval required.
gia_run_patrolExecute a patrol or audit pack — read-only posture checks that produce findings or compliance evidence. Classification: ADVISORY for low/moderate sensitivity, MANDATORY for high sensitivity. REJECTS remediation/hardening packs (use gia_apply_pack for those). Audit packs produce deterministic pass/fail per NIST control — no AI interpretation.