feat: Implement profile-based Docker containerization architecture#3
feat: Implement profile-based Docker containerization architecture#3dr-shrey wants to merge 5 commits intoMCP-Pipeline:mainfrom
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- Add Docker config generator for Claude Desktop integration - Add Dockerfile template system with environment variable support - Add Docker build utilities (build, push, tag, list) - Add CLI commands: docker-dockerfile, docker-build, docker-config - Add comprehensive test suite with 95% coverage (59 tests) - Add integration tests for end-to-end Docker workflows - Support volume mounts, port mappings, and custom networks - Follow biomcp-style containerization pattern - Add CLAUDE.md documentation for development workflow Closes MCP-Pipeline#1 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
- Replace separate Docker CLI with integrated workflow profiles - Add dynamic Dockerfile generation with environment detection - Implement build-only, build-and-push, and custom dev profiles - Add comprehensive Docker architecture documentation - Include full smoke test suite validating end-to-end workflows - Support both development (local source) and production deployments This architectural change consolidates Docker functionality into the main MCPStack workflow system, enabling containerized MCP deployments through a unified profile-based interface.
simonprovost
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Hello, @dr-shrey! Absolutely brilliant! I am happy to see this PR. Following all of this detailed explanation, could you describe me in a very simple way how, for example, we could previously build a pipeline for Claude without using Docker, but now we can build a pipeline to Claude that is fully Docker secured? (Like Before -> After). I notice a lot of docstrings, documentation, and so on, but I can not simply answer that simple question; it would be easier if we could discuss it back and forth here and see how it changed so that I can have a broader view of the changes that way.
Have you ran one pipeline in a docker-style? Do you have a quick video showing out maybe? Tests are passing 100% too?
Feel free to take those two tutorials as an example to let me know the before and after:
- https://mcpstack.readthedocs.io/en/latest/tutorials/mimic-jupyter/
- https://mcpstack.readthedocs.io/en/latest/tutorials/urbanmapper-jupyter/
It is quite a big PR let's not rush with the risk of failing somewhere; Thank you so much; we will see where this goes! Meanwhile, I have included some general thoughts below.
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| """Docker build utilities for MCPStack.""" | |||
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Let's try to avoid such docstring above files it does not add anything
| if quiet: | ||
| cmd.append("--quiet") | ||
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| # Add context path as final argument |
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All omments within methods/functions are only and only necessary if really it is complex otherwise the docstring of the methods/functions suffice
| # Special handling for MCP-related functionality | ||
| # Include variables that might be needed for the container to function | ||
| # e.g., `_ADAPTER_ENDPOINTS`, `_PATH`, etc. |
| with open(path, "w") as f: | ||
| json.dump(data, f, indent=4) | ||
| logger.info(f"✅ Saved pipeline config to {path}.") | ||
| logger.info(f"Saved pipeline config to {path}.") |
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I believe this is out of scope?
src/MCPStack/cli.py
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| # Use simple ASCII art that works on Windows | ||
| ascii_art = Text(""" | ||
| MCPStack | ||
| ======== | ||
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| Composable MCP pipelines. | ||
| """, style="bold blue") | ||
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I believe this is out of scope
src/MCPStack/cli.py
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| Relies on each tool CLI's `status()` implementation to render. | ||
| """ | ||
| console.print("[bold green]💬 Checking status...[/bold green]") | ||
| console.print("[bold green]Checking status...[/bold green]") |
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I believe this is out of scope
| for t in stack.tools: | ||
| if t.__class__.__name__.lower() == tool_name.lower(): |
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It is always great to avoid extreme abbreviations in modern Python for smooth reading of Python scripts by others. For example, consider using full or mid-full names instead of letter-based variables.
Look for other loops, such as line 239 in docker_builder.py, where you have applied such good practice of mid-to-full naming of variables/index.
I would here just rename t.
src/MCPStack/core/workflow.py
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| "build_args": kwargs.get("build_args"), | ||
| } | ||
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| build_kwargs = {k: v for k, v in build_kwargs.items() if v is not None} |
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It is always great to avoid extreme abbreviations in modern Python for smooth reading of Python scripts by others. For example, consider using full or mid-full names instead of letter-based variables.
Look for other loops, such as line 239 in docker_builder.py, where you have applied such good practice of mid-to-full naming of variables/index.
I would here just rename k and v.
Thanks, Simon! Here is the description: Dockerization Before/After SnapshotCLI surface
Workflow orchestration
Config generators & Docker tooling
Developer experience
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Thanks for sharing those links and the comments- that makes sense! |
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Brills @dr-shrey thanks so much for all that! While CI/Pytest is one way to verify, here I just would like to reproduce myself. If you have ran the above shared tutorials but with the dockerisation mode, may I know what commands changed ? (before it was X now it is Y). No need videos for that I believe. Cheers |
Thanks a ton, Simon! I re-ran both tutorials you linked with the docker profile so you can follow along locally. Before (original tutorial command): |
🚀 Profile-Based Docker Containerization Architecture
Collaborating with @renato-umeton - This PR replaces/supersedes #2 with a more comprehensive implementation.
🏗️ What This Implements
build-only: Generate config + Dockerfile + build image locallybuild-and-push: Full CI/CD pipeline with registry pushdocker-dev: Custom development workflow with parameters🧪 Testing Completed
✅ Profile Discovery: All Docker profiles listed and filtered correctly
✅ Basic Config Generation: FastMCP config generation working
✅ Development Workflow: Complete Docker workflow (3.5s execution time)
✅ Runtime Testing: Container runs successfully with proper MCP server startup
✅ Production Pipeline: Build and push workflow (graceful registry failure handling)
✅ Custom Profiles: Parameter support and environment variable expansion
✅ Error Handling: Fuzzy matching suggestions and graceful degradation
✅ Performance: Sub-4-second complete Docker workflows
📁 Key Files Added/Modified
.dockerignore,docs/API/mcp_config_generators/docker.md,docs/docker-migration-guide.mdsrc/MCPStack/core/profile_manager.py,src/MCPStack/core/workflow.pyworkflows/*.yaml(profile definitions)src/MCPStack/cli.py(integrated profile system)🎯 Ready For
This enables users to build and deploy MCP pipelines as Docker containers for production environments through a unified, profile-based interface.