mcp_basic_agent

Basic MCP Agent example

This MCP Agent app shows a "finder" Agent which has access to the fetch and filesystem MCP servers.

You can ask it information about local files or URLs, and it will make the determination on what to use at what time to satisfy the request.

┌──────────┐      ┌──────────────┐
│  Finder  │──┬──▶│  Fetch       │
│  Agent   │  │   │  MCP Server  │
└──────────┘  │   └──────────────┘
              |   ┌──────────────┐
              └──▶│  Filesystem  │
                  │  MCP Server  │
                  └──────────────┘

1 App set up

First, clone the repo and navigate to the basic‑agent example:

git clone https://github.com/lastmile-ai/mcp-agent.git
cd mcp-agent/examples/basic/mcp_basic_agent

Install uv (if you don’t have it):

pip install uv

Sync mcp-agent project dependencies:

uv sync

Install requirements specific to this example:

uv pip install -r requirements.txt

2 Set up API keys

You have three options to provide secrets:

• mcp_agent.secrets.yaml (existing pattern)
• .env file (now supported)
• MCP_APP_SETTINGS_PRELOAD (secure preload; recommended for production)

Recommended for local dev (choose one):

1. .env file

cp .env.example .env
# Edit .env and set OPENAI_API_KEY / ANTHROPIC_API_KEY, etc.

2. Secrets YAML

cp mcp_agent.secrets.yaml.example mcp_agent.secrets.yaml
# Edit mcp_agent.secrets.yaml and set your API keys

3. Preload (process-scoped)

export MCP_APP_SETTINGS_PRELOAD="$(python - <<'PY'
from pydantic_yaml import to_yaml_str
from mcp_agent.config import Settings, OpenAISettings
print(to_yaml_str(Settings(openai=OpenAISettings(api_key='sk-...'))))
PY
)"
uv run main.py

3 Run locally

Run your MCP Agent app:

uv run main.py

4 [Beta] Deploy to the cloud

a. Log in to MCP Agent Cloud

uv run mcp-agent login

b. Deploy your agent with a single command

uv run mcp-agent deploy my-first-agent

During deployment, you can select how you would like your secrets managed.

c. Connect to your deployed agent as an MCP server through any MCP client

Claude Desktop Integration

Configure Claude Desktop to access your agent servers by updating your ~/.claude-desktop/config.json:

"my-agent-server": {
  "command": "/path/to/npx",
  "args": [
    "mcp-remote",
    "https://[your-agent-server-id].deployments.mcp-agent.com/sse",
    "--header",
    "Authorization: Bearer ${BEARER_TOKEN}"
  ],
  "env": {
        "BEARER_TOKEN": "your-mcp-agent-cloud-api-token"
      }
}

MCP Inspector

Use MCP Inspector to explore and test your agent servers:

npx @modelcontextprotocol/inspector

Make sure to fill out the following settings:

Setting	Value
Transport Type	SSE
SSE	https://[your-agent-server-id].deployments.mcp-agent.com/sse
Header Name	Authorization
Bearer Token	your-mcp-agent-cloud-api-token

Tip

In the Configuration, change the request timeout to a longer time period. Since your agents are making LLM calls, it is expected that it should take longer than simple API calls.