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Google Gemini 2.5 Setup Guide

Quick setup guide for using Google Gemini 2.5 models (default configuration).

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Why Gemini 2.5?

The MCP Server with LangGraph defaults to Gemini 2.5 Flash for several reasons:
  • ✅ Latest Technology - Google’s newest model family (2025)
  • ✅ Fastest Performance - Sub-second response times
  • ✅ Cost Efficient - More affordable than GPT-4 or Claude
  • ✅ Multimodal - Native support for text, images, video, audio
  • ✅ Large Context - 1M+ token context window
  • ✅ High Quality - Competitive with GPT-4o and Claude 3.5 Sonnet

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Quick Start

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1. Get API Key

  1. Visit: https://aistudio.google.com/apikey
  2. Sign in with your Google account
  3. Click “Get API key”
  4. Create a new API key or use existing one
  5. Copy the key (starts with AI...)

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2. Configure Environment

# Copy example environment file
cp .env.example .env

# Edit .env file
nano .env  # or vim .env, or use your favorite editor
Update these values: 
# LLM Provider (already set to google by default)
LLM_PROVIDER=google

# Google API Key (paste your key here)
GOOGLE_API_KEY=AIza...your-key-here

# Model (already set to latest Gemini 2.5 Flash)
MODEL_NAME=gemini-2.5-flash

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3. Test Connection

# Test Gemini connection
python examples/test_llm.py

# Expected output:
# Provider: google
# Model: gemini-2.5-flash
# ✓ LLM initialized successfully
# ✓ Response: 4

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4. Run MCP Server

# Run StreamableHTTP server
python -m mcp_server_langgraph.mcp.server_streamable

# Or run stdio server
python -m mcp_server_langgraph.mcp.server_stdio

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Gemini 2.5 Models

  • Speed: Fastest Gemini model (sub-second responses)
  • Cost: Most cost-effective
  • Context: 1M+ tokens
  • Use Cases: Production applications, chatbots, real-time apps
  • Best For: 95% of use cases
MODEL_NAME=gemini-2.5-flash
MODEL_MAX_TOKENS=8192

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gemini-2.5-pro (Most Capable)

  • Speed: Slower but more capable
  • Cost: Higher cost, premium quality
  • Context: 1M+ tokens
  • Use Cases: Complex reasoning, research, analysis
  • Best For: High-complexity tasks requiring deep reasoning
MODEL_NAME=gemini-2.5-pro
MODEL_MAX_TOKENS=8192

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Model Comparison

ModelSpeedCostQualityContextBest For
Gemini 2.5 Flash⚡⚡⚡💰⭐⭐⭐⭐1M+Production (Default)
Gemini 2.5 Pro⚡⚡💰💰💰⭐⭐⭐⭐⭐1M+Complex reasoning
Claude 3.5 Sonnet⚡⚡💰💰⭐⭐⭐⭐⭐200KCoding, analysis
GPT-4o⚡⚡💰💰⭐⭐⭐⭐128KGeneral purpose

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Pricing (Approximate)

Gemini 2.5 Flash:
  • Input: $0.075 per 1M tokens
  • Output: $0.30 per 1M tokens
  • ~4x cheaper than GPT-4o
  • ~3x cheaper than Claude 3.5
Gemini 2.5 Pro:
  • Input: $1.25 per 1M tokens
  • Output: $5.00 per 1M tokens
  • Comparable to GPT-4o pricing

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Fallback Configuration

The default configuration includes automatic fallback: 
# Primary: Gemini 2.5 Flash
MODEL_NAME=gemini-2.5-flash

# Fallbacks (in order):
ENABLE_FALLBACK=true
FALLBACK_MODELS=["gemini-2.5-pro","claude-sonnet-4-5","gpt-5.1"]
Fallback triggers:
  • Rate limits
  • API errors
  • Timeouts
  • Model unavailability

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Advanced Configuration

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Increase Context Window

# Use full 1M context (if needed)
MODEL_MAX_TOKENS=1000000

# Note: Very large context increases latency and cost

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Adjust Temperature

# More creative (0.8-1.0)
MODEL_TEMPERATURE=0.9

# More deterministic (0.0-0.3)
MODEL_TEMPERATURE=0.2

# Default balanced (0.7)
MODEL_TEMPERATURE=0.7

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Timeout Settings

# Default timeout (60 seconds)
MODEL_TIMEOUT=60

# Longer timeout for complex queries
MODEL_TIMEOUT=120

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Multimodal Capabilities

Gemini 2.5 natively supports:
  • ✅ Text - Natural language
  • ✅ Images - Image understanding and generation
  • ✅ Video - Video analysis
  • ✅ Audio - Speech and audio processing
  • ✅ Code - Programming languages

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Example: Image Analysis

from langchain_core.messages import HumanMessage

messages = [
    HumanMessage(content=[
        {"type": "text", "text": "What's in this image?"},
        {"type": "image_url", "image_url": "https://example.com/image.jpg"}
    ])
]

response = await llm.ainvoke(messages)

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Rate Limits

Free Tier:
  • 15 requests per minute
  • 1 million tokens per day
  • 1,500 requests per day
Paid Tier:
  • 360 requests per minute
  • 4 million tokens per minute
  • No daily limits
Tip: Enable fallback models to handle rate limits gracefully.

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Troubleshooting

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API Key Not Working

# Verify key is set
echo $GOOGLE_API_KEY

# Test directly
curl -X POST https://generativelanguage.googleapis.com/v1/models/gemini-2.5-flash:generateContent?key=$GOOGLE_API_KEY \
  -H 'Content-Type: application/json' \
  -d '{"contents":[{"parts":[{"text":"Hello"}]}]}'

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Rate Limit Errors

# Enable fallback to handle rate limits
ENABLE_FALLBACK=true

# Or upgrade to paid tier
# Visit: https://console.cloud.google.com/billing

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Model Not Found

# Verify model name is correct
MODEL_NAME=gemini-2.5-flash  # ✅ Correct

# Common mistakes:
# MODEL_NAME=gemini-flash-2.5     # ❌ Wrong order
# MODEL_NAME=gemini-flash         # ❌ Missing version

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Slow Responses

# Use Flash model (default)
MODEL_NAME=gemini-2.5-flash

# Reduce max tokens
MODEL_MAX_TOKENS=4096

# Increase timeout
MODEL_TIMEOUT=90

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Monitoring

Gemini usage is automatically tracked: 
# View traces in Jaeger
open http://localhost:16686

# View metrics in Prometheus
open http://localhost:9090

# Search for:
# - llm.invoke (successful calls)
# - llm.failed (failed calls)
# - llm.fallback (fallback usage)

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Switching to Other Providers

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Switch to Anthropic

export LLM_PROVIDER=anthropic
export ANTHROPIC_API_KEY=sk-ant-...
export MODEL_NAME=claude-sonnet-4-5

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Switch to OpenAI

export LLM_PROVIDER=openai
export OPENAI_API_KEY=sk-...
export MODEL_NAME=gpt-5.1

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Switch to Local (Ollama)

# Install Ollama first
curl -fsSL https://ollama.com/install.sh | sh

# Pull model
ollama pull llama3.1:8b

# Configure
export LLM_PROVIDER=ollama
export MODEL_NAME=ollama/llama3.1:8b

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Resources

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Support

  • Google AI Forum: https://discuss.ai.google.dev
  • GitHub Issues: Report issues with the agent
  • Documentation: See integrations/litellm.md for all providers
Default Configuration Summary:
  • Provider: Google
  • Model: gemini-2.5-flash
  • Fallback: gemini-2.5-pro, claude-sonnet-4-5, gpt-5.1
  • Cost: ~75% cheaper than alternatives
  • Speed: Fastest available
You’re ready to use Gemini 2.5! 🚀