This PR fixes issue:
https://github.com/openai/openai-agents-python/issues/559
By adding the tool_call_id to the RunContextWrapper prior to calling
tools. This gives the ability to access the tool_call_id in the
implementation of the tool.
### Summary:
Allows a user to do `function_tool(is_enabled=<some_callable>)`; the
callable is called when the agent runs.
This allows you to dynamically enable/disable a tool based on the
context/env.
The meta-goal is to allow `Agent` to be effectively immutable. That
enables some nice things down the line, and this allows you to
dynamically modify the tools list without mutating the agent.
### Test Plan:
Unit tests
### Summary:
This enables users to **use** MCP inside the SDK.
1. You add a list of MCP servers to `Agent`, via `mcp_server=[...]`
2. When an agent runs, we look up its MCP tools and add them to the list of tools.
3. When a tool call occurs, we call the relevant MCP server.
Notes:
1. There's some refactoring to make sure we send the full list of tools to the Runner/Model etc.
2. Right now, you could have a locally defined tool that conflicts with an MCP defined tool. I didn't add errors for that, will do in a followup.
### Test Plan:
See unit tests. Also has an end to end example next PR.
