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pietrozullo
89 lines
2.2 KiB
Plaintext
89 lines
2.2 KiB
Plaintext
---
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title: "Sampling"
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description: "Enable LLM sampling capabilities for MCP tools"
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icon: "pipette"
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---
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<Info>
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Sampling allows MCP tools to request LLM completions during their execution.
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</Info>
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## Configuration
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To enable sampling, provide a `sampling_callback` function when initializing the MCPClient:
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<CodeGroup>
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```python Python
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from mcp_use.client import MCPClient
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from mcp.client.session import ClientSession
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from mcp.types import (
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CreateMessageRequestParams,
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CreateMessageResult,
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ErrorData,
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TextContent
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)
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async def sampling_callback(
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context: ClientSession,
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params: CreateMessageRequestParams
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) -> CreateMessageResult | ErrorData:
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"""
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Your sampling callback implementation.
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This function receives a prompt and returns an LLM response.
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"""
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# Integrate with your LLM of choice (OpenAI, Anthropic, etc.)
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response = await your_llm.complete(params.messages[-1].content.text)
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return CreateMessageResult(
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content=TextContent(text=response, type="text"),
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model="your-model-name",
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role="assistant"
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)
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# Initialize client with sampling support
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client = MCPClient(
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config="config.json",
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sampling_callback=sampling_callback
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)
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```
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</CodeGroup>
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## Creating Sampling-Enabled Tools
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When building MCP servers, tools can request sampling using the context parameter:
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```python
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from fastmcp import Context, FastMCP
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mcp = FastMCP(name="MyServer")
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@mcp.tool
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async def analyze_sentiment(text: str, ctx: Context) -> str:
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"""Analyze the sentiment of text using the client's LLM."""
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prompt = f"""Analyze the sentiment of the following text as positive, negative, or neutral.
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Just output a single word - 'positive', 'negative', or 'neutral'.
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Text to analyze: {text}"""
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# Request LLM analysis through sampling
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response = await ctx.sample(prompt)
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return response.text.strip()
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```
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## Error Handling
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If no sampling callback is provided but a tool requests sampling:
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<CodeGroup>
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```python Python
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# Without sampling callback
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client = MCPClient(config="config.json") # No sampling_callback
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# Tool that requires sampling will return an error
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result = await session.call_tool("analyze_sentiment", {"text": "Hello"})
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# result.isError will be True
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```
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</CodeGroup>
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