What is Semantic Kernel?
Microsoft's SDK for integrating LLMs into applications. Supports plugins, planners, and memory for building AI agents.
Searching Google Jobs with Semantic Kernel
This integration lets your Semantic Kernel agent search Google Jobs in real time via the Scavio API. The agent gets back structured JSON with job posting URLs, posting titles, SERP snippets -- ready for reasoning and decision-making.
Setup
Bash
pip install semantic-kernel requestsCode Example
Here is a complete Semantic Kernel agent that searches Google Jobs using Scavio:
Text
import semantic_kernel as sk
from semantic_kernel.functions import kernel_function
import json
import os
import requests
# Scavio has no Google Jobs endpoint. This runs a Google web search for the role. For structured listings (title, company, location, apply URL) call POST /api/v1/linkedin/search/jobs instead.
class ScavioPlugin:
@kernel_function(description="Query Google Jobs using Scavio")
def search(self, query: str) -> str:
response = requests.post(
"https://api.scavio.dev/api/v2/google",
headers={
"Authorization": "Bearer " + os.environ["SCAVIO_API_KEY"],
"Content-Type": "application/json",
},
json={"query": query},
timeout=60,
)
response.raise_for_status()
return json.dumps(response.json())
kernel = sk.Kernel()
kernel.add_plugin(ScavioPlugin(), "scavio")Full Working Example
A production-ready example with error handling:
Text
import semantic_kernel as sk
from semantic_kernel.functions import kernel_function
import json
import os
import requests
# Scavio has no Google Jobs endpoint. This runs a Google web search for the role. For structured listings (title, company, location, apply URL) call POST /api/v1/linkedin/search/jobs instead.
class ScavioPlugin:
@kernel_function(description="Query Google Jobs using Scavio")
def search(self, query: str) -> str:
response = requests.post(
"https://api.scavio.dev/api/v2/google",
headers={
"Authorization": "Bearer " + os.environ["SCAVIO_API_KEY"],
"Content-Type": "application/json",
},
json={"query": query},
timeout=60,
)
response.raise_for_status()
return json.dumps(response.json())
kernel = sk.Kernel()
kernel.add_plugin(ScavioPlugin(), "scavio")
result = await kernel.invoke("scavio", "search", query="senior ai engineer remote")
print(result)Pricing
Scavio offers a free tier with 50 credits on signup (1 credit per search). No credit card required. This is enough to build and test your Semantic Kernel integration. Paid plans start at $30/month for higher volumes.