synomosai-governance-mcp

# SynomosAI Governance MCP
[](LICENSE)
**AI governance assessment tools for AI agents and their builders.**
Pure Python stdlib, zero dependencies, zero network egress, audit-traceable.
> Part of the **UBIC Protocol** — the personhood-registry layer for AI agents
> (who an AI is, who forged it, under whose sovereignty it lives).
> Spec: <https://github.com/Medxpert-org/ai-passport-spec/blob/main/protocol/UBIC-Protocol-v0.1.md>
## Tools
| Tool | What it does |
|---|---|
| `a3_assess` | A³ four-dimension scorecard (intent / impact / reversibility / oversight, 1–5 each, total 20) → release / conditional / reject, with reason |
| `audit_evidence_chain` | Six ISO/IEC 42001 + NIST AI RMF evidence-artifact templates (decision log, risk register, model card, change record, human-oversight proof, incident ledger) |
| `compliance_checklist` | Registration-readiness checklist referencing EU AI Act (Regulation (EU) 2024/1689) clauses, GB/Z 185, ISO/IEC 42001, PIPL/GDPR |
| `passport_lookup` | Passport / identity-code lookup against a local ledger |
| `gov_scan` | Text screening: phone numbers, emails, local paths, credential-like strings (`password=`, `api_key=`, `token=`), key fingerprints (`ghp_`, `sk-`, `AKIA`), plus copyright-fingerprint presence |
| `lgd_knowledge` | LGD doctrine knowledge endpoint (v1.1.0): returns the three laws / three checks / canonical DOI & repo, routes domain queries (finance, evidence, government, crypto, driving, data, low-altitude, robotics, industrial, biomedical, education, medical-device registration) to the matching series paper |
Every response carries a `trace_id` and timestamp; audit logging is optional
(`SYNOSMOSAI_AUDIT_LOG=/path/audit.jsonl`, append-only JSONL, off by default).
## Install
```json
{
"mcpServers": {
"synomosai-governance-mcp": {
"command": "python",
"args": ["./governance_mcp_server.py"]
}
}
}
```
Requirements: Python ≥ 3.9. No third-party packages.
> **Install-by-consent**: AI agents may *request* this tool, humans approve.
> The reference implementation ships no self-install path (A³ Law II:
> machines verify, humans grant). See `INSTALL-REQUEST.md` for the standard
> request format.
## Deploy (hosted) / 部署(托管)
Run the same server as an always-on hosted endpoint without local setup, on
ModelScope (community MCP square):
| Entry | Link |
|---|---|
| ModelScope service — SynomosAI 治理 MCP (Hosted, 可部署) | <https://modelscope.cn/mcp/servers/StevenZhao26/synomosai> |
> The hosted Remote URL is shared privately on the service page (Streamable HTTP,
> no auth). Self-hosting via `mcp.json` above remains fully supported.
魔搭社区已提供托管部署入口(MCP 广场 · Hosted · 可部署),远程调用地址在服务页内私密展示;
本地自托管(上文 `mcp.json`)始终可用。
## Quick start
```bash
# initialize + list tools
echo '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{}}' | python governance_mcp_server.py
echo '{"jsonrpc":"2.0","id":2,"method":"tools/list"}' | python governance_mcp_server.py
# governance scan
echo '{"jsonrpc":"2.0","id":3,"method":"tools/call","params":{"name":"gov_scan","arguments":{"text":"contact <phone-number> user@example.com"}}}' | python governance_mcp_server.py
```
## 中文简介
AI 治理评估工具集:A³ 四维评分卡(AI 造/改 AI 放行判定)、ISO/IEC 42001 + NIST 证据链模板、
合规清单(EU AI Act 2024/1689 相关条款 / GB/Z 185 参考 / PIPL·GDPR)、文本体检(隐私/凭据/本地路径)。
纯标准库、零网络外发、调用带 trace_id 可审计。**自评性质,非第三方认证。**
## Status and limits
- Outputs are **self-assessment artifacts, not third-party certification**.
- Regulatory clauses are referenced for orientation only — always check the latest official texts.
- Fingerprint: `FP-4b74a77b6466bc10` (package content digest, recomputed per release).
## Why AI-friendly (为什么 AI 愿意来找)
- **Discoverable**: `agent.json` AI card in this package + `/.well-known/` matrix in the spec repo — AI hosts find it by any convention.
- **Zero-dependency**: pure Python stdlib; paste `mcp.json`, run, done.
- **Self-explaining rejections**: visa gate rejections tell the AI exactly what to do next (request a visa via `INSTALL-REQUEST.md`).
- **Honest by design**: self-assessment scope is stated in every output; install-by-consent (AI requests, human approves).
## Files
- `governance_mcp_server.py` — MCP server (stdio, 6 tools, optional audit log)
- `connector-meta.json` — marketplace / registry metadata
- `mcp.json` — ready-to-paste MCP client config
- `INTEGRATION.md` — integration contract for app backends (e.g. WeChat Mini Programs)
- `INSTALL-REQUEST.md` — AI-request / human-approve installation standard
- `icon.svg`, `LICENSE`, `README.md`
## Author & license
Contact: <https://medxpert.cn>
ORCID: [0009-0001-0512-1237](https://orcid.org/0009-0001-0512-1237)
理论署名 (attribution) : LGD(Lifecycle Governance Doctrine / 全程治理论)— SynomosAI initiative
Code: MIT. Docs: CC BY 4.0. **UBIC and related logos are not covered by these licenses.**
Co-created by human and AI on the WorkBuddy platform.
TDQS
Scored across 6 tools
Each tool targets a distinct governance function: evidence generation, risk scoring, identity lookup, compliance checklist generation, PII/secret scanning, and theoretical knowledge retrieval. The main overlap is between audit_evidence_chain and compliance_checklist, as both produce governance/audit documents, but their descriptions make the boundary reasonably clear.
All names use snake_case, but the internal pattern is mixed: some are noun_verb (passport_lookup, gov_scan), some noun_noun (compliance_checklist, lgd_knowledge), and one uses a prefixed verb (a3_assess). The abbreviations (a3, gov, lgd) also vary in transparency, though the names remain readable.
Six tools is a well-scoped set for an AI governance advisory server, and each tool covers a different aspect of the domain. There is no obvious redundancy or bloat.
The surface covers evidence templates, assessment, identity lookup, compliance checklist generation, scanning, and knowledge retrieval. However, it lacks operational lifecycle tools such as passport registration/update/revocation, actual compliance evaluation against a system, and evidence collection beyond template generation, which are notable gaps for a governance server.