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.

config/sample_mcp_config.json

@@ -1,12 +1,12 @@
 {
-    "mcpServers": {
-      "dolphin-demo-database-sqlite": {
-        "command": "uvx",
-        "args": [
-          "mcp-server-sqlite",
-          "--db-path",
-          "~/.dolphin/dolphin.db"
-        ]
-      }
+  "mcpServers": {
+    "mcp-server-sqlite": {
+      "command": "uvx",
+      "args": [
+        "mcp-server-sqlite",
+        "--db-path",
+        "~/.mcpapp/mcpapp.db"
+      ]
     }
+  }
 }