MCP Search Server

# MCP Azure Agent Example - "Finder" Agent This example demonstrates how to create and run a basic "Finder" Agent using Azure OpenAI model and MCP. The Agent has access to the `fetch` MCP server, enabling it to retrieve information from URLs. ## `1` App set up First, clone the repo and navigate to the mcp_basic_azure_agent example: ```bash git clone https://github.com/lastmile-ai/mcp-agent.git cd mcp-agent/examples/model_providers/mcp_basic_azure_agent ``` Install `uv` (if you don’t have it): ```bash pip install uv ``` Sync `mcp-agent` project dependencies: ```bash uv sync ``` Install requirements specific to this example: ```bash uv pip install -r requirements.txt ``` ## `2` Set up Azure OpenAI Check out the [Azure Python SDK docs](https://learn.microsoft.com/en-us/python/api/overview/azure/ai-inference-readme?view=azure-python-preview#getting-started) to obtain the following values: - `endpoint`: E.g. `https://<your-resource-name>.services.ai.azure.com/models` or `https://<your-resource-name>.cognitiveservices.azure.com/openai/deployments/<your-deployment-name>` - `api_key` Example configurations: ```yaml # mcp_agent.secrets.yaml # Azure OpenAI inference endpoint azure: default_model: gpt-4o-mini api_key: changethis endpoint: https://<your-resource-name>.cognitiveservices.azure.com/openai/deployments/<your-deployment-name> api_version: "2025-01-01-preview" # Azure OpenAI api-version. See https://aka.ms/azsdk/azure-ai-inference/azure-openai-api-versions # Azure AI inference endpoint azure: default_model: DeepSeek-V3 api_key: changethis endpoint: https://<your-resource-name>.services.ai.azure.com/models ``` To return structured outputs for Azure OpenAI endpoints, you might need to include `api_version` as '2025-01-01-preview'. Attach these values in `mcp_agent.secrets.yaml` or `mcp_agent.config.yaml` ## `3` Run locally To run the "Finder" agent, navigate to the example directory and execute: ```bash cd examples/model_providers/mcp_basic_azure_agent uv run --extra azure main.py ```