MCP server: One MCP server.

D'AUBE // BRIDGE²

@daubesonntag-dotcomMCP server · External

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

CI/CDv0.1.3MITPython
Freeno charge per call

Runs on your machine from its package; the steps are below.

What it does

  1. Reads
  2. Writes
  3. High impact

At most: creates or changes data: records, files, settings.

What it costs

Free

Odel charges nothing per call. The publisher may charge for its own service.

Runs locally over stdio

This server isn't hosted — your MCP client launches it from a package registry. Use one of the commands below, or drop the config into your client (e.g. Claude Desktop).

MCP Bundlehttps://github.com/daubesonntag-dotcom/daube-agent-bridge/releases/download/v0.1.3/daube-agent-bridge-0.1.3.mcpb

Distributed as an MCP bundle (`https://github.com/daubesonntag-dotcom/daube-agent-bridge/releases/download/v0.1.3/daube-agent-bridge-0.1.3.mcpb`) — download it and import the bundle in your MCP client.

README4 min read

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.git
cd daube-agent-bridge
python -m pip install -e ".[dev]"
daube-bridge validate examples/skill.yaml
daube-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.whl
python -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 Skill
version: 0.1.0
description: 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.py
python 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.

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