5 Things You Can Build with 244 AI Tools

March 15, 2026 · 7 min read

AiPayGen gives you 244 tools behind a single API. But what do you actually build with that? Here are five practical projects, each with working code you can run today.

Every example uses the same API base: https://api.aipaygen.com. The first 10 calls per day are free, no key needed. For heavier usage, grab an API key from $1.

1 Content Pipeline

Scrape a source, summarize it, translate it, and email the result. This is the bread and butter of content automation, and it takes four API calls (or one chain call with a 15% discount).

The flow

Scrape article → Summarize → Translate to Spanish → Email to team

# Step 1: Scrape the source
curl -X POST "https://api.aipaygen.com/scrape/website" \
  -H "x-api-key: apk_your_key" \
  -H "Content-Type: application/json" \
  -d '{"url": "https://example.com/article"}'

# Step 2: Summarize (paste the scraped text)
curl -X POST "https://api.aipaygen.com/summarize" \
  -H "x-api-key: apk_your_key" \
  -H "Content-Type: application/json" \
  -d '{"text": "...", "length": "short"}'

# Step 3: Translate to Spanish
curl -X POST "https://api.aipaygen.com/translate" \
  -H "x-api-key: apk_your_key" \
  -H "Content-Type: application/json" \
  -d '{"text": "...", "target_language": "Spanish"}'

# Step 4: Email the result
curl -X POST "https://api.aipaygen.com/email" \
  -H "x-api-key: apk_your_key" \
  -H "Content-Type: application/json" \
  -d '{"to": "[email protected]", "subject": "Daily digest", "body": "..."}'

Or use the /chain endpoint to run all four in sequence with a single request and get 15% off:

curl -X POST "https://api.aipaygen.com/chain" \
  -H "x-api-key: apk_your_key" \
  -H "Content-Type: application/json" \
  -d '{
    "steps": [
      {"tool": "scrape_website", "input": {"url": "https://example.com/article"}},
      {"tool": "summarize", "input": {"text": "$prev", "length": "short"}},
      {"tool": "translate", "input": {"text": "$prev", "target_language": "Spanish"}},
      {"tool": "email", "input": {"to": "[email protected]", "subject": "Digest", "body": "$prev"}}
    ]
  }'

2 Competitor Monitor

Scrape your competitors' websites daily. Compare what changed. Get a summary of the differences. Run it as a cron job.

import httpx, json

API = "https://api.aipaygen.com"
KEY = {"x-api-key": "apk_your_key", "Content-Type": "application/json"}

# Scrape competitor page
page = httpx.post(f"{API}/scrape/website", headers=KEY,
    json={"url": "https://competitor.com/pricing"}).json()

# Compare with yesterday's snapshot (you store these locally)
with open("yesterday.txt") as f:
    yesterday = f.read()

diff = httpx.post(f"{API}/compare", headers=KEY,
    json={"text_a": yesterday, "text_b": page["text"]}).json()

# Summarize the changes
summary = httpx.post(f"{API}/summarize", headers=KEY,
    json={"text": diff["comparison"], "length": "short"}).json()

print(summary["summary"])

# Save today's snapshot
with open("yesterday.txt", "w") as f:
    f.write(page["text"])

Total cost: ~$0.02 per competitor per day. Compare that to a $49/month SaaS monitoring tool.

3 AI Code Reviewer

Hook this into your CI pipeline. When a PR opens, send the diff to /code for analysis, then post the review as a comment.

# In your GitHub Action or CI script:
DIFF=$(gh pr diff $PR_NUMBER)

REVIEW=$(curl -s -X POST "https://api.aipaygen.com/code" \
  -H "x-api-key: apk_your_key" \
  -H "Content-Type: application/json" \
  -d "{\"code\": $(echo "$DIFF" | jq -Rs .),
       \"task\": \"Review this PR diff. Flag bugs, security issues, and style problems. Be specific about line numbers.\"}")

# Post as PR comment
gh pr comment $PR_NUMBER --body "## AI Code Review
$REVIEW"

The /code endpoint uses Claude for deep code understanding. It catches real bugs, not just lint warnings.

4 Multi-Language Chatbot

Detect what language the user is writing in, translate to English, process with your AI, then translate the response back. Works for support bots, community tools, or any global product.

import httpx

API = "https://api.aipaygen.com"
KEY = {"x-api-key": "apk_your_key", "Content-Type": "application/json"}

def chat(user_message: str) -> str:
    # Detect language
    lang = httpx.post(f"{API}/classify", headers=KEY,
        json={"text": user_message,
              "categories": ["English", "Spanish", "French", "German",
                             "Japanese", "Chinese", "Korean", "Portuguese"]}).json()
    detected = lang["classification"]

    # Translate to English if needed
    if detected != "English":
        en = httpx.post(f"{API}/translate", headers=KEY,
            json={"text": user_message, "target_language": "English"}).json()
        user_message = en["translation"]

    # Get AI response (your business logic here)
    resp = httpx.post(f"{API}/chat", headers=KEY,
        json={"message": user_message,
              "system": "You are a helpful support agent for Acme Corp."}).json()

    # Translate response back
    if detected != "English":
        back = httpx.post(f"{API}/translate", headers=KEY,
            json={"text": resp["response"],
                  "target_language": detected}).json()
        return back["translation"]

    return resp["response"]

# Works with any language
print(chat("Comment puis-je reinitialiser mon mot de passe?"))
# -> "Pour reinitialiser votre mot de passe, allez dans..."

Cost per conversation turn: ~$0.02 (4 API calls). No separate translation service subscription needed.

5 Research Assistant with Knowledge Graph

Deep research on a topic, extract named entities, then build a structured knowledge base. Perfect for competitive intelligence, academic research, or market analysis.

import httpx

API = "https://api.aipaygen.com"
KEY = {"x-api-key": "apk_your_key", "Content-Type": "application/json"}

topic = "AI agent frameworks 2026"

# Step 1: Deep research
research = httpx.post(f"{API}/research", headers=KEY,
    json={"topic": topic}).json()

# Step 2: Extract entities (people, companies, tools, concepts)
entities = httpx.post(f"{API}/extract", headers=KEY,
    json={"text": research["research"],
          "fields": ["companies", "tools", "people", "concepts"]}).json()

# Step 3: Store in knowledge base for future queries
for category, items in entities["extracted"].items():
    httpx.post(f"{API}/memory/store", headers=KEY,
        json={"key": f"{topic}/{category}",
              "value": items})

# Step 4: Query the knowledge base later
recall = httpx.post(f"{API}/memory/find", headers=KEY,
    json={"query": "what companies are building agent frameworks?"}).json()

print(recall)

The /research endpoint does multi-source web research with AI synthesis. Combined with /extract and the memory endpoints, you get a persistent, queryable knowledge graph.

All five projects use the same API key. No separate subscriptions for translation, scraping, code analysis, or research. One key, one balance, 244 tools.

What's the cost?

Content pipeline (4 calls/day): ~$0.72/month
Competitor monitor (3 calls/competitor/day): ~$0.60/competitor/month
Code reviewer (1 call/PR): ~$0.006/review
Chatbot (4 calls/turn, 100 turns/day): ~$60/month
Research assistant (4 calls/topic): ~$0.03/research session

Compare that to maintaining separate subscriptions for a scraping tool ($49/mo), a translation API ($20/mo), a code analysis tool ($15/mo), and an AI provider ($20/mo). That's $104/month in fixed costs before you make a single call.

Start building

Every example above works today. The first 10 calls per day are free, and you can test any tool in the browser without signing up.

Try Free in Browser Get API Key ($1) Browse All 244 Tools

Published March 15, 2026 · All posts · RSS feed