feat: add Qwen 2.5 agent example with configuration and implementation

examples/mcp_basic_qwen_agent/README.md

@@ -0,0 +1,23 @@
+# MCP Qwen Agent Example - "Finder" Agent
+
+This example demonstrates how to create and run a basic "Finder" Agent using Qwen models via Ollama's OpenAI-compatible API and MCP. The Agent has access to both the `fetch` and `filesystem` MCP servers, enabling it to retrieve information from URLs and the local file system.
+
+## Prerequisites
+
+- [Ollama](https://ollama.ai/) installed and running
+- Qwen model pulled in Ollama (run `ollama pull qwen2.5:32b`)
+
+## Setup
+
+Before running the agent, ensure you have Ollama installed and the Qwen models pulled:
+
+```bash
+# Install Ollama (Mac/Linux)
+curl -fsSL https://ollama.com/install.sh | sh
+
+# Start the Ollama service
+ollama serve
+
+# Pull the Qwen model (in another terminal)
+ollama pull qwen2.5:32b
+```

examples/mcp_basic_qwen_agent/main.py

@@ -0,0 +1,95 @@
+import asyncio
+import os
+import time
+
+from mcp_agent.app import MCPApp
+from mcp_agent.config import (
+    Settings,
+    LoggerSettings,
+    MCPSettings,
+    MCPServerSettings,
+    QwenSettings,
+)
+from mcp_agent.agents.agent import Agent
+from mcp_agent.workflows.llm.augmented_llm import RequestParams
+from mcp_agent.workflows.llm.augmented_llm_qwen import QwenAugmentedLLM
+
+settings = Settings(
+    execution_engine="asyncio",
+    logger=LoggerSettings(type="file", level="debug"),
+    mcp=MCPSettings(
+        servers={
+            "fetch": MCPServerSettings(
+                command="uvx",
+                args=["mcp-server-fetch"],
+            ),
+            "filesystem": MCPServerSettings(
+                command="npx",
+                args=["-y", "@modelcontextprotocol/server-filesystem"],
+            ),
+        }
+    ),
+    qwen=QwenSettings(
+        api_key="ollama",  # Default for Ollama
+        base_url="http://localhost:11434/v1",  # Ollama's OpenAI-compatible endpoint
+        default_model="qwen2.5:32b",
+    ),
+)
+
+# Settings can either be specified programmatically,
+# or loaded from mcp_agent.config.yaml/mcp_agent.secrets.yaml
+app = MCPApp(name="mcp_basic_qwen_agent")  # settings=settings)
+
+
+async def example_usage():
+    async with app.run() as agent_app:
+        logger = agent_app.logger
+        context = agent_app.context
+
+        logger.info("Current config:", data=context.config.model_dump())
+
+        # Add the current directory to the filesystem server's args
+        context.config.mcp.servers["filesystem"].args.extend([os.getcwd()])
+
+        finder_agent = Agent(
+            name="finder",
+            instruction="""You are an agent with access to the filesystem, 
+            as well as the ability to fetch URLs. Your job is to identify 
+            the closest match to a user's request, make the appropriate tool calls, 
+            and return the URI and CONTENTS of the closest match.""",
+            server_names=["fetch", "filesystem"],
+        )
+
+        async with finder_agent:
+            logger.info("finder: Connected to server, calling list_tools...")
+            result = await finder_agent.list_tools()
+            logger.info("Tools available:", data=result.model_dump())
+
+            llm = await finder_agent.attach_llm(QwenAugmentedLLM)
+            result = await llm.generate_str(
+                message="Print the contents of mcp_agent.config.yaml verbatim",
+            )
+            logger.info(f"mcp_agent.config.yaml contents: {result}")
+
+            result = await llm.generate_str(
+                message="Print the first 2 paragraphs of https://modelcontextprotocol.io/introduction",
+            )
+            logger.info(f"First 2 paragraphs of Model Context Protocol docs: {result}")
+
+            # Multi-turn conversations with specific model
+            result = await llm.generate_str(
+                message="Summarize those paragraphs in a 128 character tweet",
+                request_params=RequestParams(
+                    model="qwen2.5:32b",  # You can specify different Qwen models
+                ),
+            )
+            logger.info(f"Paragraph as a tweet: {result}")
+
+
+if __name__ == "__main__":
+    start = time.time()
+    asyncio.run(example_usage())
+    end = time.time()
+    t = end - start
+
+    print(f"Total run time: {t:.2f}s")

examples/mcp_basic_qwen_agent/mcp_agent.config.yaml

@@ -0,0 +1,26 @@
+$schema: ../../schema/mcp-agent.config.schema.json
+
+execution_engine: asyncio
+logger:
+  transports: [console, file]
+  level: debug
+  progress_display: true
+  path_settings:
+    path_pattern: "logs/mcp-agent-{unique_id}.jsonl"
+    unique_id: "timestamp" # Options: "timestamp" or "session_id"
+    timestamp_format: "%Y%m%d_%H%M%S"
+
+mcp:
+  servers:
+    fetch:
+      command: "uvx"
+      args: ["mcp-server-fetch"]
+    filesystem:
+      command: "npx"
+      args: ["-y", "@modelcontextprotocol/server-filesystem"]
+
+qwen:
+  # Ollama OpenAI-compatible API settings
+  api_key: "ollama"
+  base_url: "http://localhost:11434/v1"
+  default_model: "qwen2.5:32b"

schema/mcp-agent.config.schema.json

@@ -33,10 +33,7 @@
           "type": "string"
         }
       },
-      "required": [
-        "api_key",
-        "endpoint"
-      ],
+      "required": ["api_key", "endpoint"],
       "title": "AzureSettings",
       "type": "object"
     },
@@ -188,10 +185,7 @@
         },
         "unique_id": {
           "default": "timestamp",
-          "enum": [
-            "timestamp",
-            "session_id"
-          ],
+          "enum": ["timestamp", "session_id"],
           "title": "Unique Id",
           "type": "string"
         },
@@ -209,24 +203,14 @@
       "properties": {
         "type": {
           "default": "console",
-          "enum": [
-            "none",
-            "console",
-            "file",
-            "http"
-          ],
+          "enum": ["none", "console", "file", "http"],
           "title": "Type",
           "type": "string"
         },
         "transports": {
           "default": [],
           "items": {
-            "enum": [
-              "none",
-              "console",
-              "file",
-              "http"
-            ],
+            "enum": ["none", "console", "file", "http"],
             "type": "string"
           },
           "title": "Transports",
@@ -235,12 +219,7 @@
         },
         "level": {
           "default": "info",
-          "enum": [
-            "debug",
-            "info",
-            "warning",
-            "error"
-          ],
+          "enum": ["debug", "info", "warning", "error"],
           "title": "Level",
           "type": "string",
           "description": "Minimum logging level"
@@ -361,9 +340,7 @@
           "description": "Optional URI alias for presentation to the server"
         }
       },
-      "required": [
-        "uri"
-      ],
+      "required": ["uri"],
       "title": "MCPRootSettings",
       "type": "object"
     },
@@ -418,11 +395,7 @@
         },
         "transport": {
           "default": "stdio",
-          "enum": [
-            "stdio",
-            "sse",
-            "websocket"
-          ],
+          "enum": ["stdio", "sse", "websocket"],
           "title": "Transport",
           "type": "string",
           "description": "The transport mechanism."
@@ -580,11 +553,7 @@
         },
         "reasoning_effort": {
           "default": "medium",
-          "enum": [
-            "low",
-            "medium",
-            "high"
-          ],
+          "enum": ["low", "medium", "high"],
           "title": "Reasoning Effort",
           "type": "string"
         },
@@ -699,10 +668,7 @@
           "title": "Api Key"
         }
       },
-      "required": [
-        "host",
-        "task_queue"
-      ],
+      "required": ["host", "task_queue"],
       "title": "TemporalSettings",
       "type": "object"
     },
@@ -724,6 +690,38 @@
       },
       "title": "UsageTelemetrySettings",
       "type": "object"
+    },
+    "QwenSettings": {
+      "additionalProperties": true,
+      "description": "Settings for using Qwen models through Ollama's OpenAI-compatible API.",
+      "properties": {
+        "api_key": {
+          "anyOf": [
+            {
+              "type": "string"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "default": null,
+          "title": "Api Key"
+        },
+        "base_url": {
+          "title": "Base Url",
+          "type": "string",
+          "description": "Base URL for the Ollama API (e.g., http://localhost:11434/v1)"
+        },
+        "default_model": {
+          "default": "qwen2.5-coder-32b-instruct",
+          "title": "Default Model",
+          "type": "string",
+          "description": "Default Qwen model to use"
+        }
+      },
+      "required": ["base_url"],
+      "title": "QwenSettings",
+      "type": "object"
     }
   },
   "additionalProperties": true,
@@ -745,10 +743,7 @@
     },
     "execution_engine": {
       "default": "asyncio",
-      "enum": [
-        "asyncio",
-        "temporal"
-      ],
+      "enum": ["asyncio", "temporal"],
       "title": "Execution Engine",
       "type": "string",
       "description": "Execution engine for the MCP Agent application"
@@ -896,9 +891,21 @@
         "enable_detailed_telemetry": false
       },
       "description": "Usage tracking settings for the MCP Agent application"
+    },
+    "qwen": {
+      "anyOf": [
+        {
+          "$ref": "#/$defs/QwenSettings"
+        },
+        {
+          "type": "null"
+        }
+      ],
+      "default": null,
+      "description": "Settings for using Qwen models through Ollama's OpenAI-compatible API"
     }
   },
   "title": "MCP Agent Configuration Schema",
   "type": "object",
   "$schema": "http://json-schema.org/draft-07/schema#"
-}
+}

src/mcp_agent/config.py

@@ -282,6 +282,23 @@ class LoggerSettings(BaseModel):
     """HTTP timeout seconds for event transport"""
 
 
+class QwenSettings(BaseModel):
+    """
+    Settings for using Qwen models through Ollama's OpenAI-compatible API.
+    """
+
+    api_key: str | None = None
+    """API key for authentication."""
+
+    base_url: str
+    """Base URL for the Ollama API (e.g., http://localhost:11434/v1)."""
+
+    default_model: str = "qwen2.5-coder-32b-instruct"
+    """Default Qwen model to use."""
+
+    model_config = ConfigDict(extra="allow", arbitrary_types_allowed=True)
+
+
 class Settings(BaseSettings):
     """
     Settings class for the MCP Agent application.
@@ -331,6 +348,9 @@ class Settings(BaseSettings):
     usage_telemetry: UsageTelemetrySettings | None = UsageTelemetrySettings()
     """Usage tracking settings for the MCP Agent application"""
 
+    qwen: QwenSettings | None = None
+    """Settings for using Qwen models in the MCP Agent application"""
+
     @classmethod
     def find_config(cls) -> Path | None:
         """Find the config file in the current directory or parent directories."""