How should fullstack-ai-car-finder be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this skill.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

Crawler Summary

fullstack-ai-car-finder answer-first brief

Given description about the desired car, this app provides the listing of the desired car using crewai LLM agent. <h1 align="center">🚗 Cars Finder Agent</h1> **AI-powered used car recommendation system** that scrapes real listings from **Cars.com**, stores them in **MongoDB**, and gives smart car suggestions through **CrewAI + Nebius LLM** — all inside a clean, interactive **Streamlit** dashboard. Smartly find the best car options based on your budget, mileage needs, brand preference, and city using real-time AI reasoning and m Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

Freshness

Last checked 10/9/2026

Best For

fullstack-ai-car-finder 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 REPOS, runtime-metrics, public facts pack

Card Facts Snapshot Contract Trust

Agent DossierGITHUB REPOSSafety: 66/100

fullstack-ai-car-finder

OpenClawself-declared

Public facts

Change events

Artifacts

Freshness

Oct 9, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Oct 9, 2026

Vendor

Chinmay 3040

Artifacts

Benchmarks

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Unpublished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. Last updated 10/9/2026.

View Source

Setup snapshot

1
Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
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

Chinmay 3040

profilemedium

Observed Oct 9, 2026Source link Provenance

Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium

Observed Oct 9, 2026Source link Provenance

Security (1)

Handshake status

UNKNOWN

trustmedium

Observed unknownSource link Provenance

Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium

Observed Apr 15, 2026Source link Provenance

Release & Crawl Timeline

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

Self-declaredagent-index

Docs Update

Docs refreshed: Sign in to GitHub · GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts Archive

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

Self-declaredGITHUB REPOS

Extracted files

Examples

Snippets

Languages

python

Executable Examples

bash

CarsFinder
├── app.py          # Streamlit UI: sidebar, controls, main chat & results
├── agent.py        # Scraper, Memori setup, CrewAI+Nebius logic & handlers
├── db.py           # MongoDB client, collections, helpers & health check
├── assets/
│   └── nebius.png  # Logo shown in sidebar
├── api.env         
└── requirements.txt
└── pyproject.toml
└── README.md

text

NEBIUS_API_KEY=your_nebius_key

SCRAPEGRAPH_API_KEY=your_scrapegraph_api_key

MONGO_URI=mongodb://localhost:27017
MONGO_DB_NAME=cars_db

text

# python -m venv venv
# source venv/bin/activate        # macOS / Linux
# venv\Scripts\activate

text

pip install -r requirements.txt

text

streamlit run app.py

Docs & README

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

Self-declaredGITHUB REPOS

Docs source

GITHUB REPOS

Editorial quality

ready

Full README

<h1 align="center">🚗 Cars Finder Agent</h1>

AI-powered used car recommendation system that scrapes real listings from Cars.com, stores them in MongoDB, and gives smart car suggestions through CrewAI + Nebius LLM — all inside a clean, interactive Streamlit dashboard.

Smartly find the best car options based on your budget, mileage needs, brand preference, and city using real-time AI reasoning and memory.

🧩 Overview

Cars Finder Agent is an AI assistant that:

Scrapes real car listings from Cars.com using Scrapegraph.ai
Stores them in MongoDB
Uses CrewAI + Nebius LLM to recommend the best cars based on user requirements
Provides a clean, dark-themed Streamlit UI for interaction

The app lets users paste a Cars.com filtered search URL, scrape it, store all cars, and then ask queries like:

“Suggest Jeep under $55,000 in New York with good mileage”

✨ Features

🔍 Scrape & Save from Cars.com
- Uses ScrapegraphScrapeTool to extract:
  - title, price, mileage, location, details_url, image_url
- Data is normalized and stored in MongoDB with upserts
🤖 AI Car Recommendation Agent
- CrewAI Agent + Task with Nebius LLM
- Reads:
  - User query
  - Matching car listings from MongoDB
- Returns:
  - Short summary
  - 3–5 recommended cars
  - Next-step guidance
💾 MongoDB Storage Layer
- Collections:
  - cars_listings – car data
  - scraped_pages – which URLs already scraped
  - chat_debug – debug log of AI answers
📊 Health & Status in UI
- DB Health: DB connected (MongoDB ping OK) or error
- Total car records count
🎨 Modern Dark UI
- Custom CSS in st.markdown
- Logos for Scrapegraph, CrewAI & Memori in the header
- Sidebar sections for:
  - API keys
  - Storage & memory status
  - Workflow steps

🏗️ Architecture

User:
- Enters Nebius & Scrapegraph API keys (sidebar)

Scrape Layer (scrape_cars):

Uses ScrapegraphScrapeTool

Scrapes all car cards → JSON array

   "https://www.cars.com/new-cars/",
   "https://www.cars.com/shopping/results/?body_style_slugs%5B%5D=suv&zip=60606&maximum_distance=30&sort=best_match_desc",
   "https://www.cars.com/shopping/results/?zip=60606&maximum_distance=30&makes%5B%5D=bmw&sort=best_match_desc",
   "https://www.cars.com/shopping/results/?makes%5B%5D=mercedes_benz&zip=60606&maximum_distance=30&sort=best_match_desc",
   "https://www.cars.com/trucks/",

Normalizes fields and extracts numeric price (price_numeric)
Saves to cars_listings with upsert_cars()
Marks page as scraped in scraped_pages

UI (app.py):
- Shows answer under “Suggested for You”
- Below that, shows cars from MongoDB with:
  - Title
  - Price
  - Mileage
  - Location
  - Image (if available)
  - Link → “View on Cars.com”

🧰 Tech Stack

| Layer | Technology | |------------|-----------------------------------------------| | Frontend | Streamlit | | Agents | CrewAI | | LLM | Nebius (nebius/NousResearch/Hermes-4-70B) | | Scraper | ScrapegraphScrapeTool (Scrapegraph.ai) |
| Database | MongoDB | | Language | Python |

📂 Project Structure

CarsFinder
├── app.py          # Streamlit UI: sidebar, controls, main chat & results
├── agent.py        # Scraper, Memori setup, CrewAI+Nebius logic & handlers
├── db.py           # MongoDB client, collections, helpers & health check
├── assets/
│   └── nebius.png  # Logo shown in sidebar
├── api.env         
└── requirements.txt
└── pyproject.toml
└── README.md

🔑 Environment Setup

Create api.env:

NEBIUS_API_KEY=your_nebius_key

SCRAPEGRAPH_API_KEY=your_scrapegraph_api_key

MONGO_URI=mongodb://localhost:27017
MONGO_DB_NAME=cars_db

Create a virtualenv

# python -m venv venv
# source venv/bin/activate        # macOS / Linux
# venv\Scripts\activate

Install dependencies

pip install -r requirements.txt

Run the Streamlit app

streamlit run app.py

How to Use the App

Sidebar – API Keys & Scraping
- Enter Nebius API Key
- Enter Scrapegraph API Key
- Click “💾 Save Keys”

You will see: "Keys saved for this session" if successful

Scrape Cars.com
- In sidebar:
  - Enter User ID (e.g. user_1)

Check System Status

Under Storage & Memory Status in the sidebar:

 -  Database: Active / Unavailable

 - Memory Engine: Operational / Inactive
 
 - Total Car Records: <number>

Ask AI for Recommendations

In the main page:

Type your question in the text box, e.g.:

- “Recommend Toyota or Honda cars under $20,000 in Chicago with low mileage”

Click “Enter”
App will:
- Scrape listings using Scrapegraph.ai
- Clean the data
- Upsert into MongoDB
- Mark URL as scraped in scraped_pages

You’ll see a message like:

- Scraped & saved 35 car listings in MongoDB ✅

Contributing

Contributions, issues and feature requests are welcome! Feel free to:

Fork this repo
Create a new branch
Submit a pull request 🚀

Contract & API

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

MissingGITHUB REPOS

Endpoints

Dossier API Snapshot API Contract API Trust API

Contract coverage

Status

missing

Auth

None

Streaming

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-chinmay-3040-fullstack-ai-car-finder/snapshot"

curl -s "https://www.xpersona.co/api/v1/agents/crewai-chinmay-3040-fullstack-ai-car-finder/contract"

curl -s "https://www.xpersona.co/api/v1/agents/crewai-chinmay-3040-fullstack-ai-car-finder/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.

Self-declaredprotocol-neighbors

Github ReposUpdated 5h agoRank 70

AionUi

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

MCPOPENCLAW

Github ReposUpdated 6mo agoRank 70

activepieces

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

OPENCLAW

Github ReposUpdated 6mo agoRank 70

cherry-studio

AI productivity studio with smart chat, autonomous agents, and 300+ assistants.

MCPOPENCLAW

Github ReposUpdated 7mo agoRank 70

CopilotKit

The Frontend for Agents & Generative UI. React + Angular

OPENCLAW

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-chinmay-3040-fullstack-ai-car-finder/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-chinmay-3040-fullstack-ai-car-finder/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-chinmay-3040-fullstack-ai-car-finder/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-chinmay-3040-fullstack-ai-car-finder/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-chinmay-3040-fullstack-ai-car-finder/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-chinmay-3040-fullstack-ai-car-finder/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_REPOS",
      "generatedAt": "2026-10-09T23:51:38.767Z"
    }
  },
  "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",
    "category": "vendor",
    "label": "Vendor",
    "value": "Chinmay 3040",
    "href": "https://github.com/chinmay-3040/fullstack-ai-car-finder",
    "sourceUrl": "https://github.com/chinmay-3040/fullstack-ai-car-finder",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-10-09T19:13:38.411Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-chinmay-3040-fullstack-ai-car-finder/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-chinmay-3040-fullstack-ai-car-finder/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-10-09T19:13:38.411Z",
    "isPublic": true
  },
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on 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
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-chinmay-3040-fullstack-ai-car-finder/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-chinmay-3040-fullstack-ai-car-finder/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

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
  }
]