About knowledgepa3/gia-mcp-server
knowledgepa3/gia-mcp-server is an MCP server published by knowledgepa3 in the Security category: mCP proxy for GIA Governance — connects Claude Desktop and Claude Code to the hosted GIA governance engine.
The repository has 1 stars and 2 forks, with the last commit 7 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
git clone https://github.com/knowledgepa3/gia-mcp-serverThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
Tools (7)
assess_risk_tierEU AI Act risk classification (Unacceptable/High/Limited/Minimal)
Parameters not published.
classify_decisionMAI classification (Mandatory/Advisory/Informational) with dynamic elevation, confidence, and gate registration
Parameters not published.
evaluate_thresholdStorey Threshold escalation-rate health metric
Parameters not published.
map_complianceMap controls to NIST AI RMF, EU AI Act, ISO 42001, NIST 800-53, FedRAMP, LINDDUN, MITRE ATLAS, OMB
Parameters not published.
request_contextGoverned Context Authority — hash-verified, role-bound context envelopes
Parameters not published.
score_governanceWeighted integrity/accuracy/compliance composite against the release threshold
Parameters not published.
verify_ledgerSelf-consistency check of the in-memory hash chain from genesis (see the honesty note below)
Parameters not published.
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Security checks
- ✓README presentThe repository ships documentation.
- ✓License declaredUsable under a stated license.
- !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.
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Releases
README
GIA Governance Intelligence Automation
Enterprise AI governance through the Model Context Protocol.
GIA is a production governance engine that gives AI agents enforceable decision controls, compliance scoring, immutable audit chains, and human-in-the-loop gates. Built for organizations operating under NIST, FedRAMP, CMMC, EU AI Act, and SOC 2 requirements.
29 MCP tools. One integration point. Works with Claude Desktop, Claude Code, OpenAI Agent Builder, and any MCP-compatible client.
Quick Start
npx gia-mcp-server
Or install globally:
npm install -g gia-mcp-server
gia-mcp-server
The server connects to the hosted GIA engine at https://gia.aceadvising.com. Configure your API key:
GIA_API_KEY=your-key npx gia-mcp-server
Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"gia-governance": {
"command": "npx",
"args": ["-y", "gia-mcp-server"],
"env": {
"GIA_API_KEY": "your-key"
}
}
}
}
Claude Code
claude mcp add gia-governance -- npx -y gia-mcp-server
OpenAI Agent Builder
Point to the Streamable HTTP endpoint:
https://gia.aceadvising.com/mcp
Smithery
npx -y @smithery/cli install @knowledgepa3/gia-mcp-server --client claude
Tools
Decision Controls (MAI Framework)
| Tool | Description |
|---|---|
classify_decision |
Classify agent decisions as Mandatory, Advisory, or Informational |
approve_gate |
Human-in-the-loop approval for Mandatory gates |
evaluate_threshold |
Compute escalation health (Storey Threshold) |
score_governance |
Weighted governance scoring (Integrity, Accuracy, Compliance) |
Compliance & Audit
| Tool | Description |
|---|---|
audit_pipeline |
Query the hash-chained forensic audit ledger |
verify_ledger |
Verify SHA-256 chain integrity from genesis |
map_compliance |
Map controls to NIST AI RMF, EU AI Act, ISO 42001, NIST 800-53 |
assess_risk_tier |
EU AI Act risk tier classification |
generate_report |
Governance status reports (summary, detailed, executive) |
Knowledge Packs
| Tool | Description |
|---|---|
seal_memory_pack |
Create immutable, TTL-bound knowledge artifacts |
load_memory_pack |
Load packs with trust level and role enforcement |
transfer_memory_pack |
Governed knowledge transfer between agents |
compose_memory_packs |
Merge packs with risk contamination rules |
distill_memory_pack |
Extract governance patterns from usage history |
promote_memory_pack |
Promote packs to higher trust levels after review |
Security & Operations
| Tool | Description |
|---|---|
monitor_agents |
Agent health, repair history, failure counts |
srt_run_watchdog |
Infrastructure health probes (API, disk, memory, TLS, DB, DNS) |
srt_diagnose |
Incident diagnosis with playbook matching |
srt_approve_repair |
Human-approved repair execution |
srt_generate_postmortem |
Structured incident postmortems with TTD/TTR metrics |
Infrastructure Remediation
| Tool | Description |
|---|---|
gia_scan_environment |
Scout swarm for environment detection |
gia_list_packs |
List remediation, patrol, hardening, and audit packs |
gia_dry_run_pack |
Preview pack execution with blast radius analysis |
gia_apply_pack |
Execute remediation with mandatory human approval |
gia_run_patrol |
Read-only posture checks and compliance audits |
Impact & Value
| Tool | Description |
|---|---|
record_value_metric |
Track time saved, risks blocked, autonomy levels |
record_governance_event |
Log gates, drift prevention, violations blocked |
generate_impact_report |
Economic + governance ROI reporting |
system_status |
Engine health, uptime, configuration |
Architecture
GIA enforces governance through three layers:
- Decision Controls — MAI classification gates side effects and high-impact actions
- Step Hooks — Workflow progression control at each pipeline stage
- Kernel Hooks — Resource control at the LLM boundary, including sub-agents
Every governance action is recorded in a SHA-256 hash-chained audit ledger that can be independently verified.
Compliance Coverage
- NIST AI RMF — Risk management framework mapping
- EU AI Act — Risk tier assessment and control mapping
- ISO 42001 — AI management system alignment
- NIST 800-53 — Federal security control mapping
- CMMC 2.0 — DoD cybersecurity maturity
- FedRAMP — Federal cloud authorization
- SOC 2 — Service organization controls
About
Built by Advanced Consulting Experts (ACE) — a Service-Disabled Veteran-Owned Small Business (SDVOSB).
GIA was designed by William J. Storey III, a 17-year Information System Security Officer with experience across DoD contracts and U.S. Army Ranger Battalion operations. The same discipline applied to securing classified systems now governs AI agent workforces.
License
MIT
README copy captured when this server was indexed; it may lag the repository. The original is authoritative.