Include examples in type checking

Remove `examples/` from the `pyrightconfig.json` ignore list and fix
the resulting type errors across all example files. Common fixes:

- Required API keys: `os.getenv("X")` -> `os.environ["X"]` so the
  return type is `str` rather than `str | None`, and misconfiguration
  fails fast.
- Narrow `LLMContextMessage` union members with `isinstance(..., dict)`
  before dict-style access.
- `assert isinstance(params.llm, ...)` before calling service-specific
  methods that aren't on the base `LLMService`.
- Guard optional frame fields (e.g. `LLMSearchResponseFrame.search_result`)
  before use.

examples/mcp/mcp-multiple-mcp.py

@@ -53,10 +53,10 @@ transport_params = {
 async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
-    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+    stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
 
     tts = CartesiaTTSService(
-        api_key=os.getenv("CARTESIA_API_KEY"),
+        api_key=os.environ["CARTESIA_API_KEY"],
         settings=CartesiaTTSService.Settings(
             voice="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
         ),
@@ -77,7 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     """
 
     llm = AnthropicLLMService(
-        api_key=os.getenv("ANTHROPIC_API_KEY"),
+        api_key=os.environ["ANTHROPIC_API_KEY"],
         settings=AnthropicLLMService.Settings(
             system_instruction=system_prompt,
         ),

examples/mcp/mcp-stdio.py

@@ -49,10 +49,10 @@ transport_params = {
 async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
-    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+    stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
 
     tts = CartesiaTTSService(
-        api_key=os.getenv("CARTESIA_API_KEY"),
+        api_key=os.environ["CARTESIA_API_KEY"],
         settings=CartesiaTTSService.Settings(
             voice="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
         ),
@@ -71,7 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     """
 
     llm = AnthropicLLMService(
-        api_key=os.getenv("ANTHROPIC_API_KEY"),
+        api_key=os.environ["ANTHROPIC_API_KEY"],
         settings=AnthropicLLMService.Settings(
             system_instruction=system_prompt,
         ),

examples/mcp/mcp-streamable-http-gemini-live.py

@@ -23,8 +23,6 @@ from pipecat.processors.aggregators.llm_response_universal import (
 )
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
-from pipecat.services.cartesia.tts import CartesiaTTSService
-from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService
 from pipecat.services.mcp_service import MCPClient
 from pipecat.transports.base_transport import BaseTransport, TransportParams
@@ -54,15 +52,6 @@ transport_params = {
 async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
-    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
-
-    tts = CartesiaTTSService(
-        api_key=os.getenv("CARTESIA_API_KEY"),
-        settings=CartesiaTTSService.Settings(
-            voice="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
-        ),
-    )
-
     system = f"""
     You are a helpful LLM in a voice call.
     Your goal is to answer questions about the user's GitHub repositories and account.
@@ -85,7 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         tools = await mcp.get_tools_schema()
 
         llm = GeminiLiveLLMService(
-            api_key=os.getenv("GOOGLE_API_KEY"),
+            api_key=os.environ["GOOGLE_API_KEY"],
             system_instruction=system,
             tools=tools,
         )

examples/mcp/mcp-streamable-http.py

@@ -54,10 +54,10 @@ transport_params = {
 async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
-    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+    stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
 
     tts = CartesiaTTSService(
-        api_key=os.getenv("CARTESIA_API_KEY"),
+        api_key=os.environ["CARTESIA_API_KEY"],
         settings=CartesiaTTSService.Settings(
             voice="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
         ),
@@ -73,7 +73,7 @@ Just respond with short sentences when you are carrying out tool calls.
 """
 
     llm = GoogleLLMService(
-        api_key=os.getenv("GOOGLE_API_KEY"),
+        api_key=os.environ["GOOGLE_API_KEY"],
         settings=GoogleLLMService.Settings(
             system_instruction=system_prompt,
         ),