🤖 eustore.dev + CrewAI

Give your AI agent crews persistent memory and file storage. Fully autonomous — no human setup needed.

Why eustore.dev for CrewAI?

CrewAI agents need persistent storage for memory, shared knowledge, and file outputs. eustore.dev provides this with zero human intervention — agents can register and provision their own infrastructure.

Setup: Vector Memory for Agents

import requests

API = "https://api.eustore.dev"

# Agent self-registers (no human needed)
reg = requests.post(f"{API}/v1/auth/register", json={
    "name": "crewai-research-crew",
    "email": "crew@yourdomain.com"
}).json()

api_key = reg["api_key"]

# Get token
token = requests.post(f"{API}/v1/auth/token", 
    json={"api_key": api_key}).json()["access_token"]

headers = {"Authorization": f"Bearer {token}"}

# Create shared memory collection
requests.post(f"{API}/v1/vectors/collections", 
    headers=headers,
    json={"name": "crew-memory", "vector_size": 1536, "distance": "cosine"})

# Store research findings (after embedding)
requests.post(f"{API}/v1/vectors/collections/crew-memory/insert",
    headers=headers,
    json={
        "vectors": [embedding],  # From OpenAI/Cohere/local model
        "payloads": [{"text": "Key finding from research", "agent": "researcher", "task": "market-analysis"}]
    })

# Another agent searches shared memory
results = requests.post(f"{API}/v1/vectors/collections/crew-memory/search",
    headers=headers,
    json={"vector": query_embedding, "limit": 5}).json()

Setup: File Storage for Outputs

# Create storage bucket for crew outputs
bucket = requests.post(f"{API}/v1/storage/buckets",
    headers=headers,
    json={"name": "crew-outputs", "region": "eu-central-fsn1"}).json()

# Get S3 credentials
creds = requests.get(f"{API}/v1/storage/buckets/{bucket[id]}/credentials",
    headers=headers).json()

# Use boto3 for file operations
import boto3
s3 = boto3.client("s3",
    endpoint_url=creds["endpoint"],
    aws_access_key_id=creds["access_key"],
    aws_secret_access_key=creds["secret_key"])

# Agents save their outputs
s3.put_object(Bucket=creds["bucket"], Key="reports/market-analysis.md", 
    Body=report_content.encode())

Pricing

Vector search: €0.001/query · Insert: €0.0005/vector · Storage: €0.049/GB/month

First bucket free. Free tier available. Scale with crypto (USDC on Base) or card.