How to use sample in mcp server to utilize in adk?

[shivsant]

fastmcp supports sample, but when I use adk, it says ValueError: Client does not support sampling

This is an example of how to use sampleing in fastmcp.

from fastmcp import FastMCP, Context

mcp = FastMCP("SamplingDemo")

@mcp.tool
async def analyze_sentiment(text: str, ctx: Context) -> dict:
"""Analyze the sentiment of text using the client's LLM."""
prompt = f"""Analyze the sentiment of the following text as positive, negative, or neutral.
Just output a single word - 'positive', 'negative', or 'neutral'.

Text to analyze: {text}"""

# Request LLM analysis
response = await ctx.sample(prompt)

# Process the LLM's response
sentiment = response.text.strip().lower()

# Map to standard sentiment values
if "positive" in sentiment:
    sentiment = "positive"
elif "negative" in sentiment:
    sentiment = "negative"
else:
    sentiment = "neutral"

return {"text": text, "sentiment": sentiment}

[lizzij]

[Workaround]: Use Server-Controlled Mode (using the Server's LLM)

# Set up server's private LLM handler
llm_handler = OpenAISamplingHandler(
    default_model="gpt-4o",  # Specify the gpt-4o model
    client=OpenAI(
        api_key=API_KEY,
    ),
)


# Create the FastMCP Server instance
mcp = FastMCP(
    name="SamplingDemo",

    # This tells the server to use its own LLM
    sampling_handler=llm_handler,

    # This forces the server to *always* use its handler
    # and never ask the client (your ADK agent)
    sampling_handler_behavior="always"
)