Store CrewAI Agent Data on Tigris S3 Storage | Tigris Object Storage Documentation

This is the official CrewAI integration. Your agents can use the S3ReaderTool
to access Tigris Object Storage and read and write artifacts over an
S3‑compatible API.

Overview

Tigris gives you an S3-compatible store where agents can keep artifacts
(outputs, logs, JSON, embeddings) and multimodal data (images, PDFs, videos)
next to each other, with versioned buckets you can treat as experiment runs or
workspaces. This makes it a natural backing store for CrewAI agents that need to
read/write files, remember context across runs, or share rich artifacts with
other tools.

This is the primary getting-started tutorial for building a
CrewAI agent that talks to Tigris over its
S3-compatible API.

You will:

Prerequisites

Workflow overview

S3ReaderTool is a built-in CrewAI tool that takes
an S3-style path like s3://bucket/key, uses your CREW_AWS_* credentials and
the standard AWS_ENDPOINT_URL_S3 override to talk to Tigris’ S3-compatible
API, and returns the raw file contents to the agent. You can then let the agent
read, summarize, or transform that content while keeping the actual data in
Tigris rather than in prompts.

At a high level, you can treat a Tigris bucket as the backing store for a Crew
“workspace” per run. The pattern looks like this:

Workflow visualized

┌──────────────────────────────┐

│           Human/User         │

│  prompt + (optional) inputs  │

└──────────────┬───────────────┘

│ kickoff

v

┌──────────────────────────────┐

│            CrewAI            │

│  Crew -> Agents -> Tasks     │

└──────────────┬───────────────┘

│

│ (1) read inputs / context (docs, configs, prior artifacts)

v

┌──────────────────────────────┐        uses creds + endpoint env vars

│        S3ReaderTool           │<--------------------------------------┐

│  reads s3://bucket/prefix/... │                                       │

└──────────────┬───────────────┘                                        │

│                                                        │

v                                                        │

┌──────────────────────────────┐                                        │

│     Agent reasoning loop     │                                        │

│  - interpret task            │                                        │

│  - process docs              │                                        │

│  - produce intermediate      │                                        │

│    artifacts (json/md/etc)   │                                        │

└──────────────┬───────────────┘                                        │

│                                                        │

│ (2) write artifacts + final outputs (recommended)      │

v                                                        │

┌──────────────────────────────┐                                        │

│     S3WriterTool (or custom) │----------------------------------------┘

│  writes s3://bucket/prefix/...│

└──────────────┬───────────────┘

│

v

┌──────────────────────────────┐

│              S3              │

│  "artifact store / workspace"│

│  - inputs/                   │

│  - artifacts/ (intermediate) │

│  - final/ (deliverables)     │

│  - run.json (manifest)       │

└──────────────┬───────────────┘

│

│ return (usually just S3 URLs + short summary)

v

┌──────────────────────────────┐

│           Human/User         │

│  receives result + pointers  │

│  to s3://... outputs         │

└──────────────────────────────┘

A simple prefix layout for each Crew run might look like:

s3://<bucket>/crewai/<crew_name>/<run_id>/

├─ inputs/

├─ artifacts/

├─ final/

└─ run.json

Tutorial

0. Configuration

These variables control how CrewAI and boto3 talk to Tigris in this guide:

Variable Description Example
ACCESS_KEY Tigris access key ID tid_access_key_id
SECRET_ACCESS_KEY Tigris secret access key tsec_secret_access_key
OPENAI_API_KEY LLM provider API key sk-...
AWS_ENDPOINT_URL_S3 S3 endpoint for Tigris (picked up by boto3) https://t3.storage.dev
CREW_AWS_REGION Region hint for CrewAI S3 tools (Tigris ignores) auto
CREW_AWS_ACCESS_KEY_ID S3 access key seen by S3ReaderTool ${ACCESS_KEY}
CREW_AWS_SEC_ACCESS_KEY S3 secret key seen by S3ReaderTool ${SECRET_ACCESS_KEY}

1. Setup

pip install crewai boto3 python-dotenv crewai-tools

ACCESS_KEY=your_tigris_access_key

SECRET_ACCESS_KEY=your_tigris_secret_key

OPENAI_API_KEY=your_openai_key

AWS_ENDPOINT_URL_S3=https://t3.storage.dev

CREW_AWS_REGION=auto

CREW_AWS_ACCESS_KEY_ID=${ACCESS_KEY}

CREW_AWS_SEC_ACCESS_KEY=${SECRET_ACCESS_KEY}

2. Build the agent

This example lets the agent:

from dotenv import load_dotenv

from crewai import Agent, Task, Crew

from crewai_tools.aws.s3 import S3ReaderTool

load_dotenv()

# Initialize the tool – it will use CREW_AWS_* env vars

s3_reader_tool = S3ReaderTool()

file_reader_agent = Agent(

role="Tigris file reader",

goal="Read files from Tigris buckets over S3",

backstory="Knows how to fetch and summarize files stored in Tigris.",

tools=[s3_reader_tool],

verbose=True,

)

read_task = Task(

description="Read the file at {tigris_path} and summarize its contents.",

expected_output="A short summary of the file contents.",

agent=file_reader_agent,

)

crew = Crew(agents=[file_reader_agent], tasks=[read_task])

result = crew.kickoff(

inputs={

# Tigris bucket + key, S3-style

"tigris_path": "s3://your-bucket/source/review.txt",

}
)

print(result)

This pattern keeps the agent “LLM-first”: Tigris remains your durable backing
store, and CrewAI tools like S3ReaderTool bring objects into the agent’s
context only when needed.

Troubleshooting