Fetch.ai uAgents: AI Agent Integration for Web3

Integration with Fetch.ai

Imagine your DeFi protocol requires automatic monitoring of liquidity in Uniswap V3 pools and rebalancing positions when ETH price changes by 5%. Manual execution causes a 15-minute delay, while an agent on Fetch.ai uAgents handles it in 20 seconds — 10x faster than traditional bots on AWS Lambda. Traditional solutions require trust in a central server, have a single point of failure, and high operational costs when scaling. Fetch.ai (now part of the ASI Alliance) eliminates these issues: each agent has a cryptographic identity, and interaction is decentralized via the Almanac registry. Our team of blockchain engineers has implemented agent systems for decentralized automation — if your product requires this approach, it's a working tool, not speculation. Contact us to discuss possibilities for your project.

Practical use cases: uAgents automate supply chains (buyer agent negotiates with supplier agent), DeFi (agent monitors on-chain conditions and executes strategy), IoT (agent manages a smart device and monetizes data).

How uAgents Work

Agent Structure

uAgent is a Python process with a built-in HTTP server, a crypto identity (secp256k1 keypair), and a message protocol.

from uagents import Agent, Context, Model

class PriceRequest(Model):
    token: str
    currency: str = "USD"

class PriceResponse(Model):
    token: str
    price: float
    timestamp: int

price_oracle = Agent(
    name="price-oracle",
    seed="your-deterministic-seed-phrase-here",
    port=8001,
    endpoint=["http://localhost:8001/submit"],
)

@price_oracle.on_message(model=PriceRequest, replies=PriceResponse)
async def handle_price_request(ctx: Context, sender: str, msg: PriceRequest):
    price = await get_price_from_coingecko(msg.token, msg.currency)
    await ctx.send(sender, PriceResponse(
        token=msg.token,
        price=price,
        timestamp=int(time.time())
    ))
    ctx.logger.info(f"Sent {msg.token} price {price} to {sender}")

Each agent has a unique address like agent1q... (Bech32-encoded public key). The address is deterministic from the seed — reproducible between deployments.

Almanac: Registration and Discovery

Almanac is an on-chain registry (Fetch.ai mainchain) for agents. An agent registers its endpoint and protocols in Almanac, paying a fee in FET. Other agents find required ones by querying Almanac.

from uagents.query import query

response = await query(
    destination="agent1qxxxxTargetAgentAddress",
    message=PriceRequest(token="ETH"),
    timeout=30
)

This is a key difference from simple REST APIs: an agent doesn't know another agent's URL in advance — it finds it through a decentralized registry. The interaction protocol is verified by message signatures.

Protocols and Message Schemas

A protocol is a set of message types with a unique digest (SHA256 of the Pydantic schema). Two agents interact only if they use the same digest.

from uagents import Protocol

defi_protocol = Protocol(name="DeFiStrategy", version="1.0.0")

class ExecuteStrategy(Model):
    strategy_id: str
    params: dict
    max_slippage: float

class StrategyResult(Model):
    success: bool
    tx_hash: str | None
    error: str | None

@defi_protocol.on_message(model=ExecuteStrategy, replies=StrategyResult)
async def execute(ctx: Context, sender: str, msg: ExecuteStrategy):
    # execution logic
    ...

agent.include(defi_protocol)

How Fetch.ai Integrates with DeFi and Web3

Agent with On-Chain Interaction

from web3 import Web3
from uagents import Agent, Context

w3 = Web3(Web3.HTTPProvider("https://arbitrum-one.publicnode.com"))
agent = Agent(name="defi-executor", seed="...")

class ArbitrageOpportunity(Model):
    token_in: str
    token_out: str
    amount: float
    expected_profit: float

@agent.on_message(model=ArbitrageOpportunity)
async def execute_arbitrage(ctx: Context, sender: str, msg: ArbitrageOpportunity):
    if msg.expected_profit < MIN_PROFIT_THRESHOLD:
        ctx.logger.warning(f"Skipping low-profit opportunity: {msg.expected_profit}")
        return
    tx = build_arbitrage_tx(msg.token_in, msg.token_out, msg.amount)
    signed = w3.eth.account.sign_transaction(tx, PRIVATE_KEY)
    tx_hash = w3.eth.send_raw_transaction(signed.rawTransaction)
    ctx.logger.info(f"Executed arbitrage: {tx_hash.hex()}")

Periodic Tasks

@agent.on_interval(period=60.0)
async def monitor_positions(ctx: Context):
    positions = await fetch_open_positions(WALLET_ADDRESS)
    for pos in positions:
        if pos.health_factor < LIQUIDATION_THRESHOLD:
            await ctx.send(ALERT_AGENT_ADDRESS, LiquidationAlert(
                position_id=pos.id,
                health_factor=pos.health_factor
            ))

Why Fetch.ai for DeFi?

Autonomous agents solve tasks where human monitoring is inefficient: continuous on-chain analysis, automated conditional trades, decentralized data exchange. They reduce reaction latency to market events by four times compared to manual management. We have implemented projects where agents manage pool liquidity and optimize gas costs, saving up to 30% in fees. Want a similar result? Get a consultation — we will prepare an architecture for your case.

According to Fetch.ai documentation, Agentverse provides built-in monitoring. For high-load production, self-hosted offers more flexibility.

How Agent Development Works

The process includes five steps:

• Analytics (3–5 days). Define agent scope, protocols, and on-chain operations.
• Development (2–6 weeks). Write agent code with Web3/API integration.
• Testing. Simulate interaction in a local network with multiple agents.
• Deployment. Deploy on Agentverse or self-hosted with CI/CD.
• Monitoring. Set up logging and alerting (Grafana + Loki).

A typical project: 2 agents (monitoring + execution) with on-chain integration — 3–4 weeks. Our team with blockchain development experience has completed over 30 such projects. Contact us to evaluate your project — we will prepare a prototype within a week.

Practical Limitations

Throughput. uAgents are not a high-frequency system. A message via Almanac + HTTP has latency of 100–500 ms. Not suitable for HFT strategies. Suitable for monitoring and orchestration.

Message reliability. No built-in retry or delivery guarantees. Implement at the application level: timeout handling, acknowledge patterns.

FET for Almanac. Registration requires FET tokens (about 0.1 FET per registration). For production with dozens of agents, include this in the budget.

What Is Included in the Work

We deliver turnkey:

• Architectural documentation and agent interaction diagram
• Agent source code with comments
• Docker images and CI/CD pipeline
• Integration with on-chain smart contracts (EVM, Solana)
• Monitoring setup (Grafana + Loki) and alerting
• Training your team on the platform

Get a consultation on your project — we will prepare a prototype within a week.

Blockchain Infrastructure Deployment: Nodes, RPC, Indexing

Subgraph fell at 3:47 AM. By morning users saw outdated balances, transactions "hung" in the UI, support received 47 tickets in an hour. Cause: the handler in the subgraph failed on a transaction with a non-standard event log — and the entire index stopped. We have encountered such situations dozens of times. Our experience shows: blockchain infrastructure does not forgive gaps in observability. Guaranteeing uptime without multi-layered monitoring and fault-tolerant architecture is impossible. Over 8 years working with Ethereum, Polygon, and Solana, we have developed an approach that allows predictable deployment of infrastructure of any scale — from a single node to a multichain grid with dozens of subgraphs.

RPC Layer Architecture

Every dApp interaction with the blockchain goes through RPC — the JSON-RPC API provided by a node. Three options:

Managed providers — Alchemy, QuickNode, Infura, Ankr. Minimal operational costs, SLA, built-in monitoring. Limits: rate limits (Alchemy Free: 300 RU/sec), vendor lock, potential downtime during provider incidents. For most projects — the right choice at the start.

Self-owned nodes — full control, no rate limits, no third-party dependence. Cost: archive Ethereum node requires 2.5–3TB SSD, a strong server, and DevOps support. Sync from scratch on Ethereum via Geth/Nethermind — 3–7 days. Justified under high load or latency requirements.

Hybrid — self-owned node as primary, managed provider as fallback. Standard for protocols with high TVL. Proper load balancing can reduce costs by 20–30% compared to pure managed setup. Under high monthly request volume, hybrid saves significantly.

How to Set Up an RPC Layer Without a Single Point of Failure?

At least two providers, DNS round-robin with health check every 5 seconds, automatic fallback when latency >500 ms. In practice, this gives 99.99% availability during any provider failure. For protocols with high TVL, we recommend a custom HA-proxy (nginx or Envoy) in front of two managed providers.

Why Is a Hybrid RPC Scheme More Cost-Effective Than Pure Managed?

At high request volumes, managed providers can be very expensive; a hybrid using a self-owned node as primary and a managed fallback cuts costs significantly without losing SLA.

Ethereum Node Clients

Execution clients: Geth (most used), Nethermind (C#, fast sync), Besu (Java, enterprise), Erigon (fastest sync, efficient archive mode ~2TB instead of 3TB).

Consensus clients (post-Merge): Lighthouse (Rust), Prysm (Go), Teku (Java), Nimbus (Nim). Each node after The Merge requires a pair of execution + consensus clients.

For DevOps: eth-docker — Docker Compose configurations for all client combinations. Setting up monitoring via Grafana + Prometheus is mandatory; a standard dashboard is available in each client's repository.

The Graph: Event Indexing

The Graph Protocol — decentralized indexing. A subgraph describes which events from which contracts to index and how to transform them into a GraphQL schema.

Subgraph structure:

• subgraph.yaml — manifest: contract addresses, startBlock, events to handle
• schema.graphql — GraphQL schema of entities
• src/mapping.ts — AssemblyScript event handlers

dataSources:
  - kind: ethereum
    name: UniswapV3Pool
    network: mainnet
    source:
      address: "0x88e6A0c2dDD26FEEb64F039a2c41296FcB3f5640"
      abi: UniswapV3Pool
      startBlock: 12370624
    mapping:
      eventHandlers:
        - event: Swap(indexed address,indexed address,int256,int256,uint160,uint128,int24)
          handler: handleSwap

AssemblyScript handlers — not TypeScript. No nullable types, no closures, no many standard APIs. An error in the handler stops the subgraph indexing on that transaction. Important: add try-catch for operations that can fail (e.g., store.get() for an entity that may not exist).

How to Avoid Subgraph Indexing Stops?

Graph Node logs are monitored in real-time; on hasIndexingErrors = true an alert fires and an automatic node restart (via systemd or Kubernetes). Typical downtime on error — 150–300 seconds to recover. Additionally, for production we set up a watchdog that restarts Graph Node if subgraph lag exceeds 50 blocks.

Choosing Between Hosted Service and Decentralized Network

Graph Hosted Service (free, centralized) is deprecated in favor of Subgraph Studio + Graph Network. For production: deploy on Graph Network with GRT curation signal — the subgraph gets indexers proportional to curation.

Alternatives to The Graph: Ponder (TypeScript, self-hosted, easier to debug), Envio (ultra-fast indexer, supports EVM + non-EVM), Subsquid (TypeScript, own network), Moralis Streams (managed, webhook-based). Our experience shows: for high-load projects with unique logic, Ponder or Envio are more effective — they give full control over the process and do not require GRT tokenomics.

Webhooks and Real-Time Notifications

Alchemy Webhooks and QuickNode Streams allow receiving events in real-time via HTTP webhook or WebSocket. For monitoring addresses, new transactions, mints — this is faster than polling RPC.

Tenderly — platform for monitoring and alerts. You can set up an alert for a specific contract event, balance change, function call with certain parameters. Transaction simulation via Tenderly API is invaluable for debugging.

Monitoring and Observability

Minimum monitoring stack for a protocol:

On-chain: OpenZeppelin Defender Sentinel — watches contract events, triggers webhook or Autotask when conditions are met. Forta Network — community-maintained bots detect anomalies (large withdrawals, flash loans, governance attacks).

Infrastructure: Grafana + Prometheus for nodes, Datadog or Grafana Cloud for managed metrics. Alerts on: node is 10+ blocks behind, RPC latency >500ms, subgraph lag >100 blocks.

Uptime: Better Uptime or PagerDuty on RPC endpoint and subgraph health endpoint (The Graph provides _meta { hasIndexingErrors, block { number } }).

Why Is Monitoring Without Tenderly Insufficient?

Tenderly provides transaction simulation and detailed traces — critical for debugging subgraph and smart contract errors. Forta focuses on network anomalies, not your infrastructure. The combination of Tenderly plus a custom Grafana dashboard covers 90% of incident scenarios.

Multichain Infrastructure

A protocol on 5 chains = 5 separate RPC endpoints, 5 subgraphs, 5 monitoring configs. Manageable but requires deployment automation.

For subgraph multi-network deployment: graph deploy --network mainnet, graph deploy --network arbitrum-one etc. with a unified codebase and network-specific addresses in separate config files.

Chainlink CCIP and LayerZero for cross-chain messaging require monitoring of both chains and transactions on intermediate relayers. A reorg on the source chain after a confirmed mint on the target chain is a classic bridge problem. Solution: wait for finality (on Ethereum ~15 minutes after Merge for economic finality) before confirming on the target chain.

Infrastructure Setup Process

1. Audit current stack — determine chains, request volume, latency and availability requirements.
2. Architecture design — select providers, load balancing, redundancy.
3. Subgraph development — manifest → schema → handlers → testing on local Graph Node → deploy to testnet → mainnet.
4. Monitoring configuration — Tenderly alerts, Grafana dashboard, PagerDuty integration.
5. Documentation and runbook — what to do when: subgraph falls behind, RPC downtime, node desync.
6. Handover to operations — team training, access transfer, first month support.

What's Included

• Deployment of managed or self-hosted Ethereum, Polygon, BNB Chain nodes
• RPC layer setup with primary/fallback and load balancing
• Subgraph development and deployment for your protocol
• Monitoring connection (Tenderly, Grafana, alerts)
• Runbook and operations documentation
• Team training (up to 4 hours online)
• 30-day support after delivery

Timeline

All projects are managed in a GitHub/GitLab repository with CI/CD; configuration code stays with you. Order infrastructure deployment — we'll show how to cut costs by 20–30% without losing reliability. Get a consultation — we'll demonstrate how we deployed infrastructure for a protocol with large TVL on Ethereum and Arbitrum. Contact us.