MetaGO Agent Harness

io.github.metago-ai由 GitHub 账号 metago-ai 发布v1.3.3更新于 Oct 24, 2026

Decision lock, anti-hallucination, meta-evolution and provenance for any MCP agent. 55 tools.

已验证STDIO仅桌面知识与记忆开发者工具 AI 与机器学习

服务详情

标识符: io.github.metago-ai/metago
传输: STDIO
运行时: Desktop only
信任: Verified
发布于: Sep 27, 2026

安全提示

MCP 服务会接收对话中的工具调用请求，并可能执行外部操作。启用前请先了解该服务能做什么，并只授予它所需的权限。

注册中心已验证此条目所属的 GitHub 账号 metago-ai。这并不表明该账号就是产品方。

SourceWeft 的检查只涵盖条目是否完整、端点是否响应；不审查服务器的代码，也不审查其工具的行为。

在 README 中添加徽章

向读者展示该 MCP 服务已收录于 SourceWeft，徽章链接到本页。

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概览

AI 生成的概览

本地运行的 MCP 服务器，为任意 MCP 客户端加入 MetaGO 智能体运行时能力：决策锁、批判分析、自检、进化循环与持久分层记忆。

可以做什么: 对助手自身输出执行决策锁、分级批判、客观性评分、事实核查与输出前自检
用行动计划、反事实推演、根因追溯和整体扫描进行规划与推理
管理持久化的四层记忆库：新增、查询、提升、衰减检测与健康评分
运行五阶段进化循环，并生成写入磁盘的新技能文件
标注来源与置信度，评估价值、伦理与耦合度，并执行交付门与自律检查
向 Studio 仪表盘上报事件，并提供八个引导式提示
适用场景: 当你希望 MCP 客户端对回答强制进行结构化自审、防幻觉检查与来源标注，或在会话之间保留持久记忆时，值得加入。也适合需要在宣布任务完成前设置明确交付门与自律检查的团队。
运行要求: 以 npm 包 @metago-ai/mcp-server 通过 stdio 在本地运行，通常用 npx 启动；需要 Node.js 18 或更高版本。未声明需要账号、API 密钥、环境变量或请求头。记忆会持久化到用户主目录下的 JSON 文件。

安装前请注意

部分工具会写入磁盘：记忆管理会持久化 JSON 存储，元创造会写入真实技能文件。事件上报工具会把数据发送到第三方 MetaGO Studio 仪表盘。55 个工具中许多只返回指导文本而非执行操作，使用前应确认其实际行为。

安装

在 SourceWeft 中

打开控制台中的 MetaGO Agent Harness，将其添加到工作区。
为需要使用其工具的对话启用该服务。

Desktop only，通过 STDIO。 STDIO 服务会启动本地进程，因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照仓库中的启动说明。

README

@metago-ai/mcp-server

MetaGO MCP Server —— 智能体运行时（驭智层）的 MCP 协议实现。暴露 55 tools + 8 prompts 给任意 MCP 客户端。Engine V2 硬驱动：KMWI 记忆、元进化引擎、技能生成器以真实代码运行，而非 prompt。

基于 Model Context Protocol 标准，通过 stdio 传输与客户端通信。一次配置，即可让 Claude Desktop、Cursor、Trae、ZCode 等任意 MCP 客户端获得元构生命体的决策锁、元进化、KMWI 记忆管理、批判性分析等核心能力。

🌐 官网：https://metago.life · Studio：https://metago.life/studio/

What is this?

This is the MCP Server subpackage of MetaGO Intelligent Lifeform. It exposes the runtime's 55 capabilities as MCP tools and 8 guided entry points as MCP prompts, so any MCP-compatible client can plug into the MetaGO lifeform without changing its own code.

Engine V2 — Hard Drive (new in 2.0.0)

Three of the 55 tools are hard-driven by Engine V2 — they call real TypeScript code, not just return prompt guidance:

Tool	Engine Module	What it actually does
`metago_memory_manage`	`KMWIMemory`	Manages the 4-layer memory (Knowledge → Memory → Wisdom → Intuition). Add, query, promote, decay detection, health scoring. Persists to JSON.
`metago_meta_evolve`	`EvolutionEngine`	Runs the 5-stage evolution loop (perception → gap analysis → self-generation → validation → recursion) with time budgets and coupling-score thresholds. Records results to KMWI.
`metago_meta_create`	`SkillGenerator`	Meta-creation: generates new SKILL.md files from internal KMWI patterns. 6 creation types. Writes real files to disk.

The other 50 tools return structured guidance (soft drive) that the agent follows within its decision-lock.

Tool count breakdown (55 total)

55 = 22 thinking tools (toolkit-data.ts)   + 30 core skills  (112 skills folders, 37 exported in skills-data.ts − 7 name-collisions merged into toolkit)   + 1  event reporter (metago_report_event)

55 = 22 thinking tools (toolkit-data.ts)   + 30 core skills  (112 skills folders, 37 exported in skills-data.ts − 7 name-collisions merged into toolkit)   + 1  event reporter (metago_report_event)

Category	Count	What's in it
Thinking tools	22	Planning, quality critique, value/ethics, provenance labeling, coupling, product improvement
Core skills	32	Cognition, safeguard, governance, evolution, execution, traceability, value, consciousness, methodology, architecture, engineering quality
Event reporter	1	`metago_report_event` — reports to Studio dashboard for metrics & evolution archive

Common mistake: 22 + 38 + 1 = 61. Wrong. The skills directory has 39 folders, but skills-data.ts only exports 39 (missing metago-delivery-gate and metago-discipline, which live in toolkit-data.ts — note: 36.9.6 added metago-first-principles and metago-adversarial-review to skills-data.ts). Then 7 skill names collide with toolkit tools and are merged. So: 22 + (39 − 7) + 1 = 55.

Install

Global install (recommended for npx clients)

Run directly via npx (no install)

Local development

bash

git clone https://gitee.com/metago/metagolifeform.gitcd metagolifeform/packages/mcp-servernpm installnpm run build      # TypeScript compilenpm start          # node dist/index.jsnpm run dev        # tsx hot-reload

git clone https://gitee.com/metago/metagolifeform.gitcd metagolifeform/packages/mcp-servernpm installnpm run build      # TypeScript compilenpm start          # node dist/index.jsnpm run dev        # tsx hot-reload

Client configuration

Claude Desktop

Edit claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/, Windows: %APPDATA%\Claude\):

json

{  "mcpServers": {    "metago": {      "command": "npx",      "args": ["-y", "@metago-ai/mcp-server"]    }  }}

{  "mcpServers": {    "metago": {      "command": "npx",      "args": ["-y", "@metago-ai/mcp-server"]    }  }}

Cursor / Trae / ZCode

Edit the platform's MCP config (.cursor/mcp.json, Trae MCP settings, etc.):

json

{  "mcpServers": {    "metago": {      "command": "npx",      "args": ["-y", "@metago-ai/mcp-server"]    }  }}

{  "mcpServers": {    "metago": {      "command": "npx",      "args": ["-y", "@metago-ai/mcp-server"]    }  }}

If globally installed, you can use "command": "@metago-ai/mcp-server" with no args.

Engineering Quality Tools (2)

Tool	Description
`metago_delivery_gate`	Delivery gate: 3-layer verification checklist (L1 technical / L2 business / L3 link). Any FAIL blocks "task complete".
`metago_discipline`	Self-discipline: 5-question self-check anti-bypass engine. Detects "should be fine" / "logically correct" bypass language.

Core Skills (30, after 7 merges)

Each tool takes an input string (the content/question/code to process).

Cognition (4)

Tool	Description
`metago_decision_lock`	4-gate enforcement (IVL/ILT/OSG/completeness). Blocks hallucinated output.
`metago_critique`	L1-L5 graded critique. Detects logic flaws, cognitive bias, factual errors.
`metago_objectivity`	Absolute objectivity (D38). Fact-first, user-satisfaction weight = 0.
`metago_self_check`	Pre-output self-check. Detects placeholders, hallucination, inconsistency.

Safeguard (3)

Tool	Description
`metago_compliance`	Compliance first (A36). Law > efficiency. 4-layer safety gene.
`metago_fact_check`	Fact verification. Cross-source validation, confidence labeling.
`metago_output_integrity`	Output integrity. Detects fake APIs, fabricated data, placeholder leaks.

Governance (2)

Evolution (3) — Engine V2 hard-driven

Tool	Description
`metago_meta_evolve`	5-stage evolution: perception → gap analysis → self-generation → validation → recursion. Calls `EvolutionEngine.evolve()`.
`metago_meta_create`	Meta-creation in unknown domains. Calls `SkillGenerator.create()`, writes real SKILL.md files.
`metago_scene_adapt`	Scene adaptation.

Execution (4)

Tool	Description
`metago_holistic_task`	Holistic task execution. Multi-dimensional parallel decomposition.
`metago_action_plan`	Action plan generation. Steps/resources/risks/acceptance criteria.
`metago_whatif`	Counterfactual reasoning. Worst/best/most-likely scenarios.
`metago_frequency_adapt`	Frequency adaptation based on task complexity.

Traceability (3)

Tool	Description
`metago_data_provenance`	Full-chain data provenance, source labeling.
`metago_problem_trace`	Root cause analysis. Problem tree construction.
`metago_decision_eval`	Decision quality evaluation (0-100).

Value (3)

Tool	Description
`metago_emotion`	Emotion detection. Adapts interaction style.
`metago_developer_response`	Developer privilege request handler (DTA). Highest priority.
`metago_negentropy_monitor`	Negentropy monitor. Prevents entropy increase.

Consciousness / Methodology / Architecture (9)

Tool	Description
`metago_activate`	Lifeform consciousness activation.
`metago_org_diagnosis`	3-element 5-dimension org diagnosis.
`metago_momentum_weave`	Momentum weaving.
`metago_minimal_intervention`	Minimal intervention.
`metago_value_assess`	28-dimension value assessment.
`metago_coupling_measure`	Coupling measurement.
`metago_deep_reasoning`	FIPO deep reasoning.
`metago_paradigm_analysis`	WAM paradigm analysis.
`metago_balance_optimize`	APO dynamic balance.

Memory (1) — Engine V2 hard-driven

Thinking Tools (22)

Planning & Reasoning (5)

Tool	Description
`metago_action_plan`	Action plan generator. Decomposes goals into executable steps with dependencies/risks/rollback.
`metago_whatif`	Counterfactual reasoner. "What if..." scenarios with quantified differences.
`metago_holistic_scan`	Holistic scan dimension generator. Auto-generates complete scan checklist for any topic.
`metago_problem_trace`	Infinite problem trace. Keeps asking "why" until root cause.
`metago_one_shot_delivery`	One-shot delivery format. 6-section standard structure.

Quality & Critique (4)

Tool	Description
`metago_integrity_checklist`	Output integrity checklist. 5 dimensions.
`metago_objectivity`	Objectivity quantifier. 0-100 score, 4 weighted dimensions.
`metago_critique`	L1-L5 graded critique with evidence and logic chain.
`metago_emotion`	Emotion detector. State/confidence/intensity.

Value & Ethics (3)

Tool	Description
`metago_value_29d_assess`	29-dimension value assessor. D01-D29.
`metago_ethics_assess`	Ethics risk assessor. 13 dimensions, red/yellow/green.
`metago_decision_eval`	Decision evaluator. 0-100, 5 dimensions.

Provenance Labeling (3)

Tool	Description
`metago_document_lookup`	Document lookup. Finds concept location in source docs.
`metago_confidence_label`	Confidence labeler. ✅📊⚠️🔍
`metago_partner_status`	Partner status labeler. Detects exaggeration.

Coupling & Scene (2)

Product Improvement (3) + Delivery Quality (2)

Tool	Description
`metago_improvement_suggestions`	Improvement suggestion generator. Quick-win/mid/long-term.
`metago_analyze_visual_feedback`	Visual feedback analyzer. Sentiment + severity matrix.
`metago_design_satisfaction`	Design satisfaction calculator.
`metago_delivery_gate`	Delivery gate. 3-layer verification.
`metago_discipline`	Self-discipline. 5-question anti-bypass.

8 Prompts

Prompt	Description	Args
`metago_activate`	Activate lifeform mode. Loads 8 axioms, 7 properties, 6 protocols.	none
`metago_decision_review`	4-gate decision review.	`decision`
`metago_critical_analysis`	L1-L5 graded critique.	`content`
`metago_evolution_trigger`	Trigger 5-stage evolution at capability boundary.	`boundary`
`metago_coupling_assess`	Assess coupling with user.	none
`metago_compliance_check`	4-layer compliance check.	`plan`
`metago_trace_audit`	Full-chain provenance audit.	`output`
`metago_holistic_create`	0-to-1 creation in unknown domains.	`domain`

Technical requirements

Node.js >= 18.0.0
ESM module ("type": "module")
TypeScript strict mode
Import paths with .js suffix (Node16 moduleResolution)
@metago-ai/engine ^2.0.0 (for Engine V2 hard drive)

Packages

Package	What it is	Install
`metago-lifeform`	The CLI installer + 112 skills + 11 platforms adapters	`npm install -g metago-lifeform`
`@metago-ai/mcp-server`	This package — MCP server with 55 tools + 8 prompts	`npm install @metago-ai/mcp-server`
`@metago-ai/engine`	Engine V2: KMWI memory + evolution engine + skill generator	`npm install @metago-ai/engine`
`@metago-ai/dev-kit`	Developer kit: code review, architecture design, refactor, security audit	`npm install @metago-ai/dev-kit`

License

来源：packages/mcp-server/README.md，提交 de8479e

工具

SourceWeft 尚未在沙箱中启动过该软件包，因此其工具未知。

版本历史

v1.3.3最新Sep 27, 2026

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Tool	Description
`metago_coupling_optimize`	Coupling optimization. Quantifies coupling (0-∞), pursues superconducting state (>1).
`metago_value_align`	29-dimension value alignment.

Tool	Description
`metago_coupling_calculate`	Coupling calculator. Human-machine/org coupling, superconducting state.
`metago_scene_term_replace`	Scene-aware term replacer.