Crawler Summary

Multi-Agent-AI-Travel-Advisor answer-first brief

AI travel planner with 7 specialized agents, RAG, and tool-calling. Built with CrewAI & LangChain. Generates personalized itineraries with flights, hotels, activities, and cultural tips. Production-ready Python codebase. Multi-Agent AI Travel Planner v2.0 An AI travel planning system that combines **real-time API data** with **AI-powered analysis** to create personalized travel itineraries. Built with CrewAI, featuring 11 external API integrations and RAG for travel knowledge. Key Concepts - **3 AI Agents** handle reasoning: parsing requests, cultural knowledge, and itinerary compilation - **4 API Services** fetch real-time data: fli Capability contract not published. No trust telemetry is available yet. 50 GitHub stars reported by the source. Last updated 5/18/2026.

Freshness

Last checked 5/18/2026

Best For

Multi-Agent-AI-Travel-Advisor is best for crewai, multi-agent workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB OPENCLEW, runtime-metrics, public facts pack

Claim this agent
Agent DossierGitHubSafety: 75/100

Multi-Agent-AI-Travel-Advisor

AI travel planner with 7 specialized agents, RAG, and tool-calling. Built with CrewAI & LangChain. Generates personalized itineraries with flights, hotels, activities, and cultural tips. Production-ready Python codebase. Multi-Agent AI Travel Planner v2.0 An AI travel planning system that combines **real-time API data** with **AI-powered analysis** to create personalized travel itineraries. Built with CrewAI, featuring 11 external API integrations and RAG for travel knowledge. Key Concepts - **3 AI Agents** handle reasoning: parsing requests, cultural knowledge, and itinerary compilation - **4 API Services** fetch real-time data: fli

OpenClawself-declared

Public facts

5

Change events

1

Artifacts

0

Freshness

May 18, 2026

Verifiededitorial-contentNo verified compatibility signals50 GitHub stars

Capability contract not published. No trust telemetry is available yet. 50 GitHub stars reported by the source. Last updated 5/18/2026.

50 GitHub starsTrust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

May 18, 2026

Vendor

Kbhujbal

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. 50 GitHub stars reported by the source. Last updated 5/18/2026.

Setup snapshot

git clone https://github.com/kbhujbal/Multi-Agent-AI-Travel-Advisor.git
  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Kbhujbal

profilemedium
Observed May 18, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed May 18, 2026Source linkProvenance
Adoption (1)

Adoption signal

50 GitHub stars

profilemedium
Observed May 18, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB OPENCLEW

Extracted files

0

Examples

6

Snippets

0

Languages

python

Executable Examples

text

User Request
    |
[AI] Travel Planning Manager --- parses request into structured params
    |
[API] 4 services fetch in parallel (no AI, pure HTTP)
    |--- Flights: Amadeus + SerpApi (fallback)
    |--- Accommodation: Booking.com + Airbnb
    |--- Activities: Google Places + Viator + Yelp
    |--- Logistics: Google Maps + OpenWeatherMap + Currency + Country Info
    |
[AI] Travel Knowledge Expert --- RAG for cultural/visa/practical info
    |
[AI] Itinerary Compiler --- synthesizes ALL real data into day-by-day plan
    |
Final Itinerary (with real prices, real hotels, booking links)

bash

# Clone the project
cd "Multi Agent AI Travel Agent"

# Create and activate virtual environment
python -m venv venv
source venv/bin/activate  # macOS/Linux
# or: venv\Scripts\activate  # Windows

# Install dependencies
pip install -r requirements.txt

# Set up environment
cp .env.example .env
# Edit .env and add your API keys

bash

uvicorn backend.app:app --host 0.0.0.0 --port 8000 --reload --reload-exclude "venv/*" --reload-exclude "data/*"

bash

cd frontend
npm install
npm run dev

bash

python main.py

text

backend/
├── app.py                          # FastAPI entry point
├── config/
│   └── settings.py                 # All API keys & service URLs
├── api/
│   ├── routes.py                   # REST endpoints
│   └── websocket.py                # WebSocket + progress updates
├── services/                       # Pure API calls, NO AI
│   ├── flights/
│   │   ├── amadeus.py              # Amadeus API (primary)
│   │   ├── serpapi.py              # SerpApi Google Flights (fallback)
│   │   └── service.py              # FlightService coordinator
│   ├── accommodation/
│   │   ├── booking.py              # Booking.com via RapidAPI
│   │   ├── airbnb.py              # Airbnb via RapidAPI
│   │   └── service.py             # AccommodationService coordinator
│   ├── activities/
│   │   ├── google_places.py        # Attractions & restaurants
│   │   ├── viator.py              # Bookable tours
│   │   ├── yelp.py                # Dining recommendations
│   │   └── service.py             # ActivityService coordinator
│   ├── logistics/
│   │   ├── google_maps.py         # Directions & routes
│   │   ├── weather.py             # OpenWeatherMap
│   │   ├── currency.py            # Exchange rates
│   │   ├── country_info.py        # REST Countries + Travelbriefing
│   │   └── service.py             # LogisticsService coordinator
│   └── knowledge/
│       └── rag.py                 # ChromaDB RAG
├── agents/                         # Only 3 AI agents
│   ├── llm.py                     # Gemini LLM factory
│   ├── definitions.py             # Travel Manager, Knowledge Expert, Compiler
│   ├── tasks.py                   # Task definitions
│   └── tools.py                   # CrewAI tool wrapper (RAG only)
├── crew/
│   └── orchestrator.py            # Main pipeline
├── models/
│   └── schemas.py                 # Normalized Pydantic models
frontend/                           # React + Vite UI
data/
├── travel_knowledge/              # RAG documents (.txt)
└── chroma_db/             

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB OPENCLEW

Docs source

GITHUB OPENCLEW

Editorial quality

ready

AI travel planner with 7 specialized agents, RAG, and tool-calling. Built with CrewAI & LangChain. Generates personalized itineraries with flights, hotels, activities, and cultural tips. Production-ready Python codebase. Multi-Agent AI Travel Planner v2.0 An AI travel planning system that combines **real-time API data** with **AI-powered analysis** to create personalized travel itineraries. Built with CrewAI, featuring 11 external API integrations and RAG for travel knowledge. Key Concepts - **3 AI Agents** handle reasoning: parsing requests, cultural knowledge, and itinerary compilation - **4 API Services** fetch real-time data: fli

Full README

Multi-Agent AI Travel Planner v2.0

An AI travel planning system that combines real-time API data with AI-powered analysis to create personalized travel itineraries. Built with CrewAI, featuring 11 external API integrations and RAG for travel knowledge.

Key Concepts

  • 3 AI Agents handle reasoning: parsing requests, cultural knowledge, and itinerary compilation
  • 4 API Services fetch real-time data: flights, accommodation, activities, and logistics
  • RAG Knowledge Base provides cultural tips, visa info, and practical advice via ChromaDB
  • AI only does analysis — all travel data comes from real APIs, not hallucinated by the LLM

Architecture

User Request
    |
[AI] Travel Planning Manager --- parses request into structured params
    |
[API] 4 services fetch in parallel (no AI, pure HTTP)
    |--- Flights: Amadeus + SerpApi (fallback)
    |--- Accommodation: Booking.com + Airbnb
    |--- Activities: Google Places + Viator + Yelp
    |--- Logistics: Google Maps + OpenWeatherMap + Currency + Country Info
    |
[AI] Travel Knowledge Expert --- RAG for cultural/visa/practical info
    |
[AI] Itinerary Compiler --- synthesizes ALL real data into day-by-day plan
    |
Final Itinerary (with real prices, real hotels, booking links)

Quick Start

Prerequisites

Installation

# Clone the project
cd "Multi Agent AI Travel Agent"

# Create and activate virtual environment
python -m venv venv
source venv/bin/activate  # macOS/Linux
# or: venv\Scripts\activate  # Windows

# Install dependencies
pip install -r requirements.txt

# Set up environment
cp .env.example .env
# Edit .env and add your API keys

Running

Backend:

uvicorn backend.app:app --host 0.0.0.0 --port 8000 --reload --reload-exclude "venv/*" --reload-exclude "data/*"

Frontend (separate terminal):

cd frontend
npm install
npm run dev

CLI mode (no frontend needed):

python main.py

API Keys Required

Required

| Key | Purpose | Get it from | |-----|---------|-------------| | GEMINI_API_KEY | AI agents (needs paid plan) | aistudio.google.com/apikey |

Flight APIs (need at least one)

| Key | Purpose | Get it from | |-----|---------|-------------| | AMADEUS_API_KEY + AMADEUS_API_SECRET | Primary flight search | developers.amadeus.com | | SERPAPI_KEY | Fallback flight search | serpapi.com |

Accommodation APIs (need at least one)

| Key | Purpose | Get it from | |-----|---------|-------------| | BOOKING_API_KEY | Hotels (Booking.com via RapidAPI) | rapidapi.com | | AIRBNB_API_KEY | Rentals (Airbnb via RapidAPI) | rapidapi.com |

Activity APIs (need at least one)

| Key | Purpose | Get it from | |-----|---------|-------------| | GOOGLE_PLACES_API_KEY | Attractions & restaurants | console.cloud.google.com | | VIATOR_API_KEY | Bookable tours | docs.viator.com | | YELP_API_KEY | Dining (5,000 calls/day free) | yelp.com/developers |

Logistics APIs (all free)

| Key | Purpose | Get it from | |-----|---------|-------------| | GOOGLE_MAPS_API_KEY | Transport routes | console.cloud.google.com | | OPENWEATHER_API_KEY | Weather forecast | openweathermap.org |

Optional

| Key | Purpose | |-----|---------| | OPENAI_API_KEY | RAG embeddings (only if using knowledge base) | | EXCHANGE_RATE_API_KEY | Currency rates (fallback uses free API without key) |

Services gracefully skip any provider whose key isn't configured.

Project Structure

backend/
├── app.py                          # FastAPI entry point
├── config/
│   └── settings.py                 # All API keys & service URLs
├── api/
│   ├── routes.py                   # REST endpoints
│   └── websocket.py                # WebSocket + progress updates
├── services/                       # Pure API calls, NO AI
│   ├── flights/
│   │   ├── amadeus.py              # Amadeus API (primary)
│   │   ├── serpapi.py              # SerpApi Google Flights (fallback)
│   │   └── service.py              # FlightService coordinator
│   ├── accommodation/
│   │   ├── booking.py              # Booking.com via RapidAPI
│   │   ├── airbnb.py              # Airbnb via RapidAPI
│   │   └── service.py             # AccommodationService coordinator
│   ├── activities/
│   │   ├── google_places.py        # Attractions & restaurants
│   │   ├── viator.py              # Bookable tours
│   │   ├── yelp.py                # Dining recommendations
│   │   └── service.py             # ActivityService coordinator
│   ├── logistics/
│   │   ├── google_maps.py         # Directions & routes
│   │   ├── weather.py             # OpenWeatherMap
│   │   ├── currency.py            # Exchange rates
│   │   ├── country_info.py        # REST Countries + Travelbriefing
│   │   └── service.py             # LogisticsService coordinator
│   └── knowledge/
│       └── rag.py                 # ChromaDB RAG
├── agents/                         # Only 3 AI agents
│   ├── llm.py                     # Gemini LLM factory
│   ├── definitions.py             # Travel Manager, Knowledge Expert, Compiler
│   ├── tasks.py                   # Task definitions
│   └── tools.py                   # CrewAI tool wrapper (RAG only)
├── crew/
│   └── orchestrator.py            # Main pipeline
├── models/
│   └── schemas.py                 # Normalized Pydantic models
frontend/                           # React + Vite UI
data/
├── travel_knowledge/              # RAG documents (.txt)
└── chroma_db/                     # Vector store (auto-generated)
main.py                             # CLI entry point

How It Works

The Pipeline (2-3 AI calls instead of 15-20)

  1. AI Step 1 — Travel Manager parses natural language into structured parameters (destinations, dates, budget, interests)
  2. API Step — 4 services fetch real data in parallel via asyncio.gather (flights, hotels, activities, logistics) — pure HTTP, no AI
  3. AI Step 2 — Knowledge Expert queries RAG for cultural/visa/practical info
  4. AI Step 3 — Itinerary Compiler takes ALL real API data + knowledge and creates a personalized day-by-day plan

Adding Travel Knowledge

Add .txt files to data/travel_knowledge/. Delete data/chroma_db/ to force re-indexing. The RAG system automatically indexes new documents on next run.

Tech Stack

  • CrewAI — Multi-agent orchestration
  • Google Gemini — LLM (via LiteLLM)
  • FastAPI — REST + WebSocket API
  • httpx — Async HTTP client for all API services
  • ChromaDB — Vector database for RAG
  • React + Vite — Frontend
  • Pydantic — Data models and validation

Troubleshooting

"Rate limit error" / "429" / "RESOURCE_EXHAUSTED"

Your Gemini free tier quota is exhausted. Enable billing at aistudio.google.com or wait for daily reset.

"API key expired"

Generate a new key at aistudio.google.com/apikey and update .env.

Server reloads during execution

Run with: uvicorn backend.app:app --reload --reload-exclude "venv/*" --reload-exclude "data/*"

"ModuleNotFoundError"

Activate your venv and run: pip install -r requirements.txt

ChromaDB errors

Delete data/chroma_db/ and run again.

License

MIT License — see LICENSE for details.

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB OPENCLEW

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://www.xpersona.co/api/v1/agents/crewai-kbhujbal-multi-agent-ai-travel-advisor/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-kbhujbal-multi-agent-ai-travel-advisor/contract"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-kbhujbal-multi-agent-ai-travel-advisor/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

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Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://www.xpersona.co/api/v1/agents/crewai-kbhujbal-multi-agent-ai-travel-advisor/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-kbhujbal-multi-agent-ai-travel-advisor/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-kbhujbal-multi-agent-ai-travel-advisor/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-kbhujbal-multi-agent-ai-travel-advisor/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-kbhujbal-multi-agent-ai-travel-advisor/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-kbhujbal-multi-agent-ai-travel-advisor/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-10-09T01:08:25.212Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "crewai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "multi-agent",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:crewai|supported|profile capability:multi-agent|supported|profile"
}

Facts JSON

[
  {
    "factKey": "vendor",
    "label": "Vendor",
    "value": "Kbhujbal",
    "category": "vendor",
    "href": "https://github.com/kbhujbal/Multi-Agent-AI-Travel-Advisor",
    "sourceUrl": "https://github.com/kbhujbal/Multi-Agent-AI-Travel-Advisor",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-05-18T06:45:19.357Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "protocols",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "category": "compatibility",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-kbhujbal-multi-agent-ai-travel-advisor/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-kbhujbal-multi-agent-ai-travel-advisor/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-05-18T06:45:19.357Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "traction",
    "label": "Adoption signal",
    "value": "50 GitHub stars",
    "category": "adoption",
    "href": "https://github.com/kbhujbal/Multi-Agent-AI-Travel-Advisor",
    "sourceUrl": "https://github.com/kbhujbal/Multi-Agent-AI-Travel-Advisor",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-05-18T06:45:19.357Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "docs_crawl",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "category": "integration",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "handshake_status",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "category": "security",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-kbhujbal-multi-agent-ai-travel-advisor/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-kbhujbal-multi-agent-ai-travel-advisor/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true,
    "metadata": {}
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true,
    "metadata": {}
  }
]

Sponsored

Ads related to Multi-Agent-AI-Travel-Advisor and adjacent AI workflows.