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# SynomosAI Governance MCP

[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](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

B3.3/5.0

Scored across 6 tools

Disambiguation4/5

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.

Naming Consistency3/5

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.

Tool Count5/5

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.

Completeness3/5

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.

Maintenance

ActivityMaintained
ResponsivenessNo recent community issues