Find agent skills by outcome

- `ctx.log_info(message

data)` / `ctx.log_error()` / `ctx.log_debug()` - Logging

- `ctx.report_progress(progress

message)` - Report progress for long operations

Coding & Debugging

return await api_call(resource_id

api_key)

async def interactive_tool(resource_id: str

ctx: Context) -> str:

await ctx.report_progress(0.75

Formatting results...)

await ctx.log_info(Processing query

{query: query

from mcp.server.fastmcp import FastMCP

Context

Creative

await ctx.report_progress(0.25

Starting search...)

async def advanced_search(query: str

ctx: Context) -> str:

lines = [f# User Search Results: '{params.query}'

return json.dumps(response

indent=2)

Communication

'''Search for users in the Example system by name

if isinstance(e

httpx.HTTPStatusError):

elif isinstance(e

httpx.TimeoutException):

Coding & Debugging

async def _make_api_request(endpoint: str

method: str = GET

def validate_query(cls

v: str) -> str:

offset: Optional[int] = Field(default=0

description=Number of results to skip for pagination

response_format: ResponseFormat = Field(default=ResponseFormat.MARKDOWN

description=Output format)

limit: Optional[int] = Field(default=20

description=Maximum results to return

class ResponseFormat(str

Enum):

Communication

query: str = Field(...

description=Search string to match against names/emails

from typing import Optional

List

from pydantic import BaseModel

Field

Communication

email: str

# Email address (e.g.