chore: import upstream snapshot with attribution

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+# Model Context Protocol
+
+The [Model Context Protocol (MCP)](https://modelcontextprotocol.io/introduction) is an open standard that enables developers to build secure, two-way connections between their data sources and AI-powered tools.
+
+The API can be configured to handle MCP requests. All enabled endpoints set in the API configuration are automatically added as MCP tools.
+
+```yaml
+mcp: boolean|dict
+```
+
+When `mcp` is a boolean, default arguments are used. When `mcp` is a dictionary it supports the following options.
+
+```yaml
+mcp:
+  clientargs: http client options (dict)
+  mcpargs: FastApiMCP options (dict)
+```
+
+See the following links for details on the options.
+
+- [HTTP Client Arguments](https://www.python-httpx.org/api/#asyncclient)
+- [FastApiMCP Arguments](https://github.com/tadata-org/fastapi_mcp/blob/main/fastapi_mcp/server.py#L22)
+
+Once this configuration option is added, a new route is added to the application `/mcp`. 
+
+The [Model Context Protocol Inspector tool](https://www.npmjs.com/package/@modelcontextprotocol/inspector) is a quick way to explore how the MCP tools are exported through this interface.
+
+Run the following and go to the local URL specified.
+
+```
+npx @modelcontextprotocol/inspector node build/index.js
+```
+
+Enter `http://localhost:8000/mcp` to see the full list of tools available.