Add MCP server adapter for structured agent tool access - #23
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Arun Sekhar (achandmsft) wants to merge 1 commit into
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Add MCP server adapter for structured agent tool access#23Arun Sekhar (achandmsft) wants to merge 1 commit into
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| Clone this repo and open it alongside your app as a [multi-root workspace](https://code.visualstudio.com/docs/editor/multi-root-workspaces): | ||
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| ```bash | ||
| git clone https://github.com/Azure-Samples/azure-openai-to-responses.git | ||
| # File → Add Folder to Workspace… → select azure-openai-to-responses | ||
| ``` | ||
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| The `@azure-openai-to-responses` agent and skill activate automatically. |
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I believe this is clumsy. Switching from single root to multi-root workspaces impact the experience in vscode: a lot of the extensions start asking you "which workspace" either on start or when running a command.
We should probably look for alternatives. Also I'm not sure that works for GH CP CLI users
Add mcp_server.py exposing scan, smoke_test, check_models, and migration_plan as structured MCP tools (stdio transport). Agents call these natively instead of shelling out to CLI scripts. - Add mcp optional dependency to pyproject.toml - Add azure-openai-to-responses-mcp console script entry point - Add MCP server docs and repo structure update to README
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What this does
Adds
mcp_server.pyexposing the scanner, smoke test, model compatibility checker, and migration plan as structured MCP tools (stdio transport). Agents call these natively instead of shelling out to CLI scripts.scansmoke_testcheck_modelsmigration_planAlso adds:
mcpoptional dependency in pyproject.tomlazure-openai-to-responses-mcpconsole script entry pointWhy
Scripts as entry point means agents shell out via
executeand parse stdout. MCP gives structured I/O and works in sandboxed environments whereexecuteis disabled.Related