What is Semantic Kernel?
Microsoft's SDK for integrating LLMs into applications. Supports plugins, planners, and memory for building AI agents.
Searching X (Twitter) with Semantic Kernel
This integration lets your Semantic Kernel agent search X (Twitter) in real time via the Scavio API. The agent gets back structured JSON with post snippets, author handles, timestamps, engagement signals — ready for reasoning and decision-making.
Setup
Bash
pip install semantic-kernel requestsCode Example
Here is a complete Semantic Kernel agent that searches X (Twitter) using Scavio:
Text
import semantic_kernel as sk
from semantic_kernel.functions import kernel_function
import requests
import json
class ScavioPlugin:
@kernel_function(description="Search X (Twitter) using Scavio")
def search(self, query: str) -> str:
response = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": "your_scavio_api_key", "Content-Type": "application/json"},
json={"query": query},
)
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 requests
import json
class ScavioPlugin:
@kernel_function(description="Search X (Twitter) using Scavio")
def search(self, query: str) -> str:
response = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": "your_scavio_api_key", "Content-Type": "application/json"},
json={"query": query},
)
return json.dumps(response.json())
kernel = sk.Kernel()
kernel.add_plugin(ScavioPlugin(), "scavio")
# Use the plugin
result = await kernel.invoke("scavio", "search", query="site:x.com AI agents 2026")
print(result)Pricing
Scavio offers a free tier with 500 credits/month (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.