feat: Implement async utilities for MCP server management and JSON-RPC communication

- Added `process.py` for managing MCP server subprocesses with async capabilities.
- Introduced `protocol.py` for handling JSON-RPC communication over streams.
- Created `llm_client.py` to support chat completion requests to various LLM providers, integrating with MCP tools.
- Defined model configurations in `llm_models.py` for different LLM providers.
- Removed the synchronous `mcp_manager.py` in favor of a more modular approach.
- Established a provider framework in `providers` directory with a base class and specific implementations.
- Implemented `OpenAIProvider` for interacting with OpenAI's API, including streaming support and tool call handling.

pyproject.toml

@@ -61,6 +61,7 @@ lint.select = [
     "T10",  # flake8-debugger
     "A",  # flake8-builtins
     "UP",  # pyupgrade
+    "TID", # flake8-tidy-imports
 ]
 
 lint.ignore = [
@@ -81,7 +82,7 @@ skip-magic-trailing-comma = false
 combine-as-imports = true
 
 [tool.ruff.lint.mccabe]
-max-complexity = 12
+max-complexity = 16
 
 [tool.ruff.lint.flake8-tidy-imports]
 # Disallow all relative imports.