OmniSerp 🔍

A Unified Search Engine Abstraction for AI Agents

The Problem ⚠️

AI agents need real-time information

  • 🧠 LLMs have knowledge cutoffs
  • 📅 Static training data becomes stale
  • 👤 Users expect current, accurate answers
  • 🌐 Agents must access live web data

The Challenge 🧩

Search API fragmentation

  • 🔀 Multiple providers: Serper.dev, SerpApi, Google, Bing
  • 📋 Each has different APIs, parameters, response formats
  • 🔧 Switching providers requires extensive code changes
  • ⚙️ Different providers support different operations
  • ❌ No standardized interface exists

Why Web Search Matters for Agents 🤖

Grounding AI in Reality

Capability Without Search With Search
Current events ❌ Limited ✅ Real-time
Fact verification ⚠️ Hallucination risk ✅ Verified
Research tasks ❌ Incomplete ✅ Comprehensive
Local information ❌ None ✅ Available

Web Search Enables 🚀

Critical Agent Capabilities

  • 📰 Real-time information: News, stock prices, weather
  • ✅ Fact verification: Reduce hallucinations with sources
  • 📚 Research: Academic papers, documentation, tutorials
  • 📍 Local context: Places, maps, business reviews
  • 👁️ Visual search: Image analysis via reverse search (Lens)
  • 🛒 Shopping: Product comparisons and pricing

Meet the Providers 🤝

Serper.dev ⚡

  • 🚀 Fast Google Search API
  • 📦 Simple JSON responses
  • 🔢 12 search operations supported
  • 👁️ Includes Google Lens support
  • 🔐 POST-based API with header authentication

Meet the Providers 🤝

SerpApi 🔬

  • 📊 Comprehensive search API
  • 🌍 Multiple search engines supported
  • 🔢 11 search operations (no Lens)
  • 🔑 GET-based API with query auth
  • 📋 Structured, detailed responses

Feature Comparison 📊

Operation Serper SerpApi
🌐 Web Search ✅ ✅
📰 News ✅ ✅
🖼️ Images ✅ ✅
🎬 Videos ✅ ✅
📍 Places ✅ ✅
🗺️ Maps ✅ ✅
🛒 Shopping ✅ ✅
🎓 Scholar ✅ ✅
👁️ Lens ✅ ❌

The Solution: OmniSerp 💡

One interface, multiple providers

// Same code works with any provider
client := omniserp.New()
result, _ := client.Search(ctx, params)

// Switch providers at runtime
client.SetEngine("serpapi")

Architecture Overview 🏗️

flowchart TB A["🤖 Your Application / Agent"] --> B["📦 OmniSerp Client SDK
Unified Interface
Capability Checking
Response Normalization"] B --> C["⚡ Serper
Engine"] B --> D["🔬 SerpApi
Engine"] C --> E["serper.dev"] D --> F["serpapi.com"] classDef app fill:#7c4dff,stroke:#667eea,color:#fff classDef sdk fill:#00bfa5,stroke:#00897b,color:#fff classDef engine fill:#ff7043,stroke:#e64a19,color:#fff classDef api fill:#78909c,stroke:#546e7a,color:#fff class A app class B sdk class C,D engine class E,F api

Why a Generic Interface? 🔌

Problem 1: Provider Lock-in 🔒

Without abstraction:

  • ⛓️ Code tightly coupled to one provider
  • 🔄 Switching requires rewriting everything
  • 🧪 Testing requires live API calls

With OmniSerp:

  • ✨ Swap providers with one line change
  • 🎭 Mock engines for testing
  • 🛡️ Graceful fallbacks

Why a Generic Interface? 🔌

Problem 2: Feature Parity ⚖️

// Check capabilities at runtime
if client.SupportsOperation(OpSearchLens) {
    result, _ := client.SearchLens(ctx, params)
} else {
    // Fallback strategy
}

🤖 Agents can adapt behavior based on available features

Why a Generic Interface? 🔌

Problem 3: Response Inconsistency 🔀

Raw responses differ between providers:

// Serper
{"answerBox": {...}}

// SerpApi
{"answer_box": {...}}

✅ OmniSerp normalizes to a unified structure

Normalized Responses 📐

Engine-agnostic data structures

normalized, _ := client.SearchNormalized(ctx, params)

// Same fields regardless of provider
for _, result := range normalized.OrganicResults {
    fmt.Println(result.Title)
    fmt.Println(result.Link)
    fmt.Println(result.Snippet)
}

The Engine Interface ⚙️

Clean abstraction

type Engine interface {
    GetName() string
    GetSupportedTools() []string

    Search(ctx, params) (*SearchResult, error)
    SearchNews(ctx, params) (*SearchResult, error)
    SearchImages(ctx, params) (*SearchResult, error)
    // ... 12 operations total
}

➕ Adding a new provider = implement this interface

Real-World Applications 🌍

1. MCP Server for AI Assistants 🤖

# Claude Desktop integration
./mcpserver
# Registers 12 tools for Serper
# Registers 11 tools for SerpApi

💬 Enables Claude to search the web natively

Real-World Applications 🌍

2. Multi-Provider Redundancy 🛡️

result, err := client.Search(ctx, params)
if err != nil {
    client.SetEngine("serpapi") // Fallback
    result, _ = client.Search(ctx, params)
}

✅ Never fail because one API is down

Real-World Applications 🌍

3. Cost Optimization 💰

  • 📊 Use different providers for different query types
  • 📈 Route high-volume queries to cheaper provider
  • ⭐ Reserve premium features for when needed

Benefits Summary ✨

For Agent Developers

  • 🎯 Simplicity: One API to learn
  • 🔄 Flexibility: Switch providers easily
  • 🛡️ Reliability: Built-in fallbacks
  • 🔮 Future-proof: Add providers without code changes
  • 🔒 Type safety: Strongly-typed Go interfaces

Getting Started 🚀

Quick setup

export SERPER_API_KEY="your-key"
# or
export SERPAPI_API_KEY="your-key"

import "github.com/agentplexus/omniserp/client"

c, _ := client.New()
result, _ := c.Search(ctx, omniserp.SearchParams{
    Query: "latest AI news",
})

The Future 🔮

Extensible by design

  • ➕ Easy to add new providers (Bing, DuckDuckGo, etc.)
  • 🔌 Plugin architecture ready
  • 👥 Community contributions welcome
  • 🌱 Growing ecosystem of AI tools

Summary 📋

OmniSerp solves

  1. 🔀 Search API fragmentation → unified interface
  2. 🔒 Provider lock-in → runtime switching
  3. 📐 Response inconsistency → normalization layer
  4. ⚖️ Feature gaps → capability checking
  5. 🤖 Agent integration → MCP server included

Thank You 🙏

OmniSerp 🔍

github.com/agentplexus/omniserp

🌐 Unified search for the AI agent era