SDK Examples
Copy-paste examples to get started in seconds. All endpoints work with the free tier (10 calls/day) -- no API key needed to try.
Install:
pip install requests1. Single Tool Call
Call any endpoint with a simple POST request.
sentiment.pyAnalyze sentiment of any text
import requests
BASE = "https://aipaygen.com"
# API_KEY = "your-api-key" # Optional: omit for free tier (10/day)
resp = requests.post(f"{BASE}/sentiment", json={
"text": "I love building with AI agents! The future is bright."
}, headers={
# "X-API-Key": API_KEY, # Uncomment for paid tier
})
data = resp.json()
print(f"Polarity: {data['polarity']}")
print(f"Score: {data['score']}")
print(f"Emotions: {data.get('emotions', [])}")
2. Tool Chain
Chain multiple AI operations. Each step can use $prev.result from the previous step.
chain.pyResearch, summarize, then translate
import requests
BASE = "https://aipaygen.com"
resp = requests.post(f"{BASE}/chain", json={
"steps": [
{"tool": "research", "input": {"query": "x402 payment protocol"}},
{"tool": "summarize", "input": {"text": "$prev.result", "format": "bullets"}},
{"tool": "translate", "input": {"text": "$prev.result", "target": "Spanish"}}
]
})
data = resp.json()
for step in data["chain"]:
print(f"Step {step['step']} ({step['tool']}): {step['time_ms']}ms")
print(f"\nFinal result:\n{data['final_result']}")
3. Streaming Response
Stream long responses token-by-token for real-time output.
stream.pyStream a chat response
import requests
BASE = "https://aipaygen.com"
resp = requests.post(f"{BASE}/chat", json={
"messages": [{"role": "user", "content": "Explain quantum computing"}],
"stream": True
}, stream=True)
for line in resp.iter_lines():
if line:
text = line.decode("utf-8")
if text.startswith("data: "):
print(text[6:], end="", flush=True)
print() # Final newline
Install:
pip install aipaygen-mcp1. Quick Start
The SDK wraps all 244 tools as Python methods.
quickstart.pySDK basics
from aipaygen_mcp import AiPayGenClient
client = AiPayGenClient(
base_url="https://aipaygen.com",
api_key="your-api-key" # Or omit for free tier
)
# Sentiment analysis
result = client.sentiment("I love this product!")
print(result)
# Web search
results = client.search("x402 protocol", n=5)
for r in results:
print(f" {r['title']}: {r['url']}")
# Code generation
code = client.code("fibonacci function", language="python")
print(code)
2. Chain Operations
Build multi-step workflows with the SDK.
sdk_chain.pyChain with the SDK
from aipaygen_mcp import AiPayGenClient
client = AiPayGenClient(base_url="https://aipaygen.com")
# Chain: research -> summarize -> translate
result = client.chain([
{"tool": "research", "input": {"query": "AI agent payments"}},
{"tool": "summarize", "input": {"text": "$prev.result"}},
{"tool": "translate", "input": {"text": "$prev.result", "target": "French"}}
])
print(f"Completed in {result['total_time_ms']}ms")
print(result["final_result"])
3. MCP Server Mode
Run as an MCP server for Claude Desktop, Cursor, or any MCP client.
TerminalStart the MCP server
# Install and run
pip install aipaygen-mcp
aipaygen-mcp --api-key YOUR_KEY
# Or connect to remote MCP
# URL: https://mcp.aipaygen.com/mcp
No dependencies needed -- uses built-in
fetch1. Single Tool Call
sentiment.jsAnalyze sentiment
const BASE = "https://aipaygen.com";
// const API_KEY = "your-api-key"; // Optional
const resp = await fetch(`${BASE}/sentiment`, {
method: "POST",
headers: {
"Content-Type": "application/json",
// "X-API-Key": API_KEY, // Uncomment for paid tier
},
body: JSON.stringify({
text: "I love building with AI agents!"
})
});
const data = await resp.json();
console.log(`Polarity: ${data.polarity}, Score: ${data.score}`);
2. Tool Chain
chain.jsMulti-step chain
const resp = await fetch("https://aipaygen.com/chain", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
steps: [
{ tool: "research", input: { query: "x402 payment protocol" } },
{ tool: "summarize", input: { text: "$prev.result", format: "bullets" } },
{ tool: "translate", input: { text: "$prev.result", target: "Japanese" } }
]
})
});
const { chain, final_result, total_time_ms } = await resp.json();
chain.forEach(s => console.log(`Step ${s.step} (${s.tool}): ${s.time_ms}ms`));
console.log(`\nResult (${total_time_ms}ms):\n${final_result}`);
3. Streaming
stream.jsStream chat responses
const resp = await fetch("https://aipaygen.com/chat", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
messages: [{ role: "user", content: "Explain quantum computing" }],
stream: true
})
});
const reader = resp.body.getReader();
const decoder = new TextDecoder();
while (true) {
const { done, value } = await reader.read();
if (done) break;
const text = decoder.decode(value);
for (const line of text.split("\n")) {
if (line.startsWith("data: ")) {
process.stdout.write(line.slice(6));
}
}
}
Works with any terminal. No API key needed for free tier.
1. Sentiment Analysis
sentiment
curl -s https://aipaygen.com/sentiment \
-H "Content-Type: application/json" \
-d '{"text": "AI agents are the future!"}' | python3 -m json.tool
2. Web Search
search
curl -s https://aipaygen.com/search \
-H "Content-Type: application/json" \
-d '{"query": "x402 protocol", "n": 3}' | python3 -m json.tool
3. Code Generation
code
curl -s https://aipaygen.com/code \
-H "Content-Type: application/json" \
-d '{"description": "REST API server with Express", "language": "javascript"}'
4. Chain Operations
chain
curl -s https://aipaygen.com/chain \
-H "Content-Type: application/json" \
-d '{
"steps": [
{"tool": "research", "input": {"query": "quantum computing"}},
{"tool": "summarize", "input": {"text": "$prev.result"}}
]
}' | python3 -m json.tool
5. With API Key
authenticatedUse your API key for higher limits
# Generate an API key first
curl -s https://aipaygen.com/auth/generate-key \
-H "Content-Type: application/json" \
-d '{"name": "my-app"}'
# Then use it in requests
curl -s https://aipaygen.com/research \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_KEY_HERE" \
-d '{"question": "What is the x402 payment protocol?"}'
Install:
pip install langchain requestsCustom Tool Integration
Wrap AiPayGen endpoints as LangChain tools for use in agents.
langchain_tools.pyAiPayGen as LangChain tools
import requests
from langchain.tools import Tool
from langchain.agents import initialize_agent, AgentType
from langchain_openai import ChatOpenAI
BASE = "https://aipaygen.com"
API_KEY = "your-api-key"
HEADERS = {"Content-Type": "application/json", "X-API-Key": API_KEY}
def aipaygen_search(query: str) -> str:
"""Search the web using AiPayGen."""
r = requests.post(f"{BASE}/search", json={"query": query, "n": 5}, headers=HEADERS)
return str(r.json())
def aipaygen_summarize(text: str) -> str:
"""Summarize text using AiPayGen."""
r = requests.post(f"{BASE}/summarize", json={"text": text}, headers=HEADERS)
return r.json().get("summary", str(r.json()))
def aipaygen_sentiment(text: str) -> str:
"""Analyze sentiment using AiPayGen."""
r = requests.post(f"{BASE}/sentiment", json={"text": text}, headers=HEADERS)
return str(r.json())
# Define LangChain tools
tools = [
Tool(name="WebSearch", func=aipaygen_search,
description="Search the web for current information"),
Tool(name="Summarize", func=aipaygen_summarize,
description="Summarize a long text into key points"),
Tool(name="Sentiment", func=aipaygen_sentiment,
description="Analyze the sentiment of text"),
]
# Create an agent
llm = ChatOpenAI(model="gpt-4")
agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION)
# Run it
result = agent.run("Search for 'x402 protocol', then summarize what you find")
print(result)
Works with Claude Desktop, Cursor, Windsurf, and any MCP client
1. MCP Setup (claude_desktop_config.json)
Add AiPayGen as an MCP server in your Claude Desktop config.
claude_desktop_config.jsonAdd to your MCP config
{
"mcpServers": {
"aipaygen": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.aipaygen.com/mcp"
]
}
}
}
2. Local MCP Server
Install and run locally for lower latency.
Local install
# Install from PyPI
pip install aipaygen-mcp
# Run the MCP server
aipaygen-mcp --api-key YOUR_KEY
# Or add to claude_desktop_config.json:
# {
# "mcpServers": {
# "aipaygen": {
# "command": "aipaygen-mcp",
# "args": ["--api-key", "YOUR_KEY"]
# }
# }
# }
3. Usage in Claude
Once configured, just ask Claude to use AiPayGen tools naturally.
Example promptsWhat to say to Claude
# In Claude Desktop / Cursor / Claude Code, just say:
"Use aipaygen to search for the latest AI agent news"
"Analyze the sentiment of this customer review: ..."
"Research x402 protocol, summarize it, and translate to French"
"Generate a Python REST API with authentication"
"Scrape https://example.com and extract the main topics"
# Claude will automatically call the right AiPayGen MCP tools!
4. Smithery (One-Click Install)
SmitheryInstall via Smithery registry
# Install via Smithery CLI
npx @smithery/cli install Damien829/Aipaygen
# Or visit: https://smithery.ai/servers/Damien829/Aipaygen