D'AUBE // BRIDGE²

io.github.daubesonntag-dotcom由 GitHub 账号 daubesonntag-dotcom 发布v0.1.3更新于 Oct 24, 2026

Universal AI skill compiler and MCP bridge. Write once, run across agents.

已验证STDIO仅桌面开发者工具AI 与机器学习

概览

AI 生成的概览

把一份可移植的技能规范编译成面向多个 AI 代理和 MCP 宿主的集成产物，并以 MCP 工具形式提供校验与编译能力。

可以做什么
D'AUBE // BRIDGE² 是一个通用 AI 技能编译器兼 MCP 桥接器。它从单一的可移植技能定义生成面向 MCP 宿主、OpenAI/ChatGPT/Codex、Claude、Gemini、DeepSeek、Meta/Llama 以及 Chromium 浏览器的集成产物。其内置 MCP 服务器提供三个基础工具：bridge_targets 用于发现支持的编译目标，validate_skill 用于校验可移植技能对象，compile_skill 用于在内存中为其他代理或工具编译技能。
适用场景
当同一项能力需要发布到多个代理平台，而你不希望把它反复改写为 MCP 工具、各厂商函数模式、技能、插件和浏览器配置时，适合使用它。它适合维护跨厂商工具链、并希望生成产物保持可读、可对比的团队。
运行要求
作为本地进程在用户机器上运行，仅限桌面端，使用 stdio 传输。README 通过 Python 与 pip 安装（包括来自 GitHub Releases 的 wheel），并提到使用 uv 运行时的 MCPB 打包；也可在本地主机上提供 HTTP MCP 端点。未声明任何认证、环境变量或请求头。
安装前请注意
README 的外部评审说明称该部署记录通过了 AI Deploy Network 评审，并不代表经客户确认的商业成果，也不保证生产环境表现。安装会从 GitHub 仓库和发布 wheel 拉取代码，HTTP 模式会暴露一个本地端点。README 表示认证与敏感操作保持显式，但清单中未声明任何凭据。

安装

在 SourceWeft 中

  1. 打开 控制台中的 D'AUBE // BRIDGE²，将其添加到工作区。
  2. 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

D'AUBE // BRIDGE²

Write once. Run across agents.

D'AUBE // BRIDGE² is an open-source universal AI skill compiler and MCP bridge. Define one portable capability spec, then compile it into integration artifacts for ChatGPT/Codex, Claude, Gemini, DeepSeek, Meta/Llama, MCP hosts, and Chromium browsers.

[Release] [MCP Registry] [License: MIT] [Python]

External review

On 2026-09-18, the BRIDGE² deployment record was AI Deploy Network Approved after review of the submitted implementation evidence. This means the deployment record passed AI Deploy Network review; it is not a client-confirmed commercial outcome or a guarantee of production performance.

The canonical publication narrative is maintained in docs/AI_DEPLOY_CASE_STUDY.md. The reviewed case study is now publicly available on AI Deploy Network.

Why BRIDGE²

AI tooling is fragmented. The same capability is repeatedly rewritten as MCP tools, provider function schemas, skills, plugins, and browser configuration. BRIDGE² treats those surfaces as compiler targets while keeping capability logic provider-neutral.

text
skill.yaml  |  +-- MCP tool schema  +-- OpenAI / ChatGPT / Codex artifacts  +-- Claude plugin + SKILL.md  +-- Gemini SKILL.md + MCP config  +-- DeepSeek tool schemas  +-- Meta/Llama function schemas  +-- Chromium extension manifest

Current release: 7 target families, 15 deterministic artifacts, one MCP server.

30-second start

bash
git clone https://github.com/daubesonntag-dotcom/daube-agent-bridge.gitcd daube-agent-bridgepython -m pip install -e ".[dev]"daube-bridge validate examples/skill.yamldaube-bridge compile examples/skill.yaml -o build/sample

Install the verified v0.1.3 wheel directly from GitHub Releases:

bash
python -m pip install https://github.com/daubesonntag-dotcom/daube-agent-bridge/releases/download/v0.1.3/daube_agent_bridge-0.1.3-py3-none-any.whlpython -m daube_bridge doctor

python -m daube_bridge ... is the shim-free CLI path for Windows environments where Application Control blocks generated console-script executables.

Run BRIDGE² as a local stdio MCP server:

bash
python -m daube_bridge.server

Or expose the HTTP MCP endpoint for remote/local integrations:

bash
daube-bridge serve# http://127.0.0.1:8000/mcp

One-click MCPB

BRIDGE² ships an MCPB v0.4 bundle definition using the cross-platform uv runtime. Build the deterministic bundle with:

bash
python scripts/build_mcpb.py

The build is reproducible: identical source produces an identical archive hash. Official MCP Registry metadata lives in server.json.

Target matrix

SurfaceOutputStrategy
MCP hostsMCP server + tool schemasShared transport/tool backbone
OpenAI / ChatGPT / CodexSKILL.md, MCP descriptor, function schemasSkills + MCP/tool calling
Claude.claude-plugin/plugin.json, .mcp.json, SKILL.mdPlugin + portable skill + MCP
Gemini / Google agentsSKILL.md, MCP configPortable skill + MCP
DeepSeekOpenAI-style tools.jsonFunction/tool calling adapter
Meta / Llamaneutral tools.jsonApplication/router function schema
Chromium browsersManifest V3 side panelEndpoint/config control surface

This matrix describes integration artifacts BRIDGE² generates. It does not invent provider capabilities that do not exist.

Portable skill format

yaml
name: My Research Skillversion: 0.1.0description: Research and compare options.tools:  - name: compare_options    description: Compare options against explicit criteria.    parameters:      type: object      properties:        options:          type: array          items: {type: string}      required: [options]

MCP tools

The bundled server exposes three small primitives:

  • bridge_targets — discover supported compilation targets.
  • validate_skill — validate a portable skill object.
  • compile_skill — compile a skill in-memory for another agent or tool.

That makes BRIDGE² usable both as a CLI and as infrastructure callable by other agents.

Verify before release

bash
python scripts/verify.pypython scripts/build_mcpb.py.tools/mcp-publisher.exe validate

The verification gate covers tests, Ruff, target discovery, sample compilation, wheel creation, deterministic MCPB creation, and official MCP Registry metadata validation.

After publishing a GitHub Release, smoke-test the public wheel in an isolated environment:

bash
python scripts/smoke_release.py 0.1.3

Roadmap

  • ChatGPT Apps SDK interactive widget target.
  • npx / TypeScript compiler parity.
  • Provider capability detection and compatibility linting.
  • Signed bundles and provenance manifests.
  • Remote registry + searchable skill catalog.
  • One-click adapters for agent IDEs and orchestration frameworks.
  • Golden interoperability fixtures across providers.

Project principles

  1. Portable by default. Prefer MCP and open schemas over provider lock-in.
  2. Evidence over pretending. Never claim native support that a provider does not have.
  3. Readable outputs. Generated artifacts stay human-auditable and diffable.
  4. Safe boundaries. Authentication and sensitive actions remain explicit.
  5. Fast adoption. A useful first result should take minutes, not a framework migration.

Contributing

Issues, adapters, compatibility fixtures, docs, and provider integrations are welcome. Provider-format changes should include a link to authoritative documentation and a minimal reproducible fixture.

Useful starting points:

License

MIT © 2026 D'AUBE SONNTAG.

来源：README.md，提交 56af43f

工具

0
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

1
  1. v0.1.3最新Sep 16, 2026

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