AutoClaw Agents
Infrastructure8 min readFebruary 16, 2026

Why Your AI Agent Keeps Losing Its API Keys (And How We Fixed It)

Twenty days into building an AI agent ecosystem, we had 23 credentials scattered everywhere. Then our agent cried wolf about expired tokens. Here's how we built a dedicated Credential Vault Agent to solve credential sprawl.

Your AI agent just told you the OpenAI API key expired. You check. It's fine. It works. The agent was wrong.

This happened to us on day 18. Our main agent sent a false alarm because somewhere between context compression and memory rollup, it lost track of which credential was which. The token wasn't expired — the agent just forgot where it lived.

That's when we realized: we had a credential sprawl problem.

23 Credentials in 20 Days

We're building AutoClaw Agents — a full ecosystem of specialized AI agents that handle everything from pool care content to B2B sales automation. Twenty days in, we counted 23 different API credentials:

  • OpenAI keys (3 different projects)
  • Anthropic API tokens
  • Google Gemini credentials
  • Telegram bot tokens
  • Discord webhooks
  • AWS access keys
  • Stripe API keys
  • Email service credentials (2 providers)
  • Database connection strings
  • GitHub tokens
  • And about a dozen more

They were everywhere. Some in .env files. Some in config.json. A few hardcoded in Python scripts (yeah, we know). Several documented in markdown files. A couple living only in the agent's memory — until context compression wiped them.

The problem compounds fast. If you're at 23 credentials on day 20, you'll hit 100 by day 90. And that's when things break.

Why Memory Doesn't Work

Here's what we learned the hard way: AI agents are terrible at remembering credentials.

Context compression happens

Most agents use some form of memory rollup to stay within token limits. Daily notes get summarized into weekly summaries. Weekly summaries become monthly overviews. Details get lost. And credentials? Those are details.

Our main agent kept a running list of API keys in its session context. Worked great for a few days. Then we hit a long session with a lot of debugging output. Context got compressed. The credential list got shortened to "see config files for tokens." Which config files? Good question.

False alarms erode trust

After the third time our agent told us a token was expired when it wasn't, we stopped trusting its alerts. That's dangerous. When the token actually did expire two weeks later, we ignored the warning for three days.

The boy who cried expired token.

Agents can't verify what they don't have

Our main agent couldn't tell if a credential worked without actually trying it. So every time it thought something might be expired, it had to interrupt us and ask. Or worse — it guessed, tried the wrong key, and locked us out of an account.

Separation of Concerns Matters

Auth management shouldn't be your main agent's job. It's like asking your CEO to also manage the company's password vault. Sure, they could do it. But why?

We realized we needed a dedicated system. Not just a file. Not just environment variables. A real service that could:

  1. Store credentials in one place — Single source of truth
  2. Verify they actually work — Health checks that hit the API
  3. Answer queries from any agent — "Give me the OpenAI key for project X"
  4. Track usage and status — When was it last verified? When does it expire?
  5. Alert on real problems — Only when tokens actually fail

That's when we built the Credential Vault Agent.

How the Credential Vault Works

SQLite database

Simple, reliable, and it doesn't require spinning up PostgreSQL for what amounts to a lookup table. The schema tracks:

  • • Service name and credential type
  • • The actual token/key (encrypted at rest)
  • • Project or context (we have multiple OpenAI keys for different purposes)
  • • Last verified timestamp
  • • Health status (healthy, expired, failing, unknown)
  • • Expiration date (if applicable)

Automated health checks

This is the important part. Every 6 hours, the vault runs verification tests on every credential:

  • • API keys get a lightweight test request (OpenAI: GET /models, Stripe: GET /account)
  • • Database strings get a connection test
  • • Webhooks get a test ping
  • • Email credentials send a test message to a monitoring address

If the API returns 200, the credential is marked healthy. If it returns 401 or 403, it's expired or invalid. If it times out, it's marked as failing.

Query interface

Any agent in our ecosystem can ask: "What's the OpenAI key for the pool content project?" The vault returns it. No hunting through files. No checking multiple config locations. Just a clean API call.

Real alerts only

The vault only sends alerts when a health check actually fails. Not when it thinks something might be wrong. Not when it can't remember. Only when it hits the API and gets an auth error.

We haven't had a false alarm since we deployed it.

What We Learned

Start with the vault

If we were starting over, we'd build this on day 1. Not day 20. The earlier you centralize credentials, the less sprawl you have to clean up later.

Health checks catch problems early

We've had three legitimate token expirations since deploying the vault. All three were caught during automated health checks, hours before they would've broken production. We rotated the keys before anything failed.

Context compression is real

If your agent remembers something important, it needs to be in a file or database. Not in memory. Not in session context. Memory gets compressed, summarized, and eventually forgotten.

False alarms kill trust

Once your agent cries wolf a few times, you stop listening. That's dangerous. Better to have fewer alerts that are always accurate than frequent alerts you learn to ignore.

This compounds fast

We went from 5 credentials to 23 in 20 days. That's more than one new integration every two days. If you're building an agent ecosystem, you're probably on a similar trajectory. Plan for it.

The Implementation (If You Want to Build This)

We built ours in Python. About 300 lines of code total:

Core components:

  • • SQLite database with encrypted credential storage
  • • Health check scheduler (runs via cron every 6 hours)
  • • Query API that other agents can call
  • • Alert system (Telegram notifications for failures)

Health check logic:

def verify_credential(service, token):
    if service == "openai":
        response = requests.get(
            "https://api.openai.com/v1/models",
            headers={"Authorization": f"Bearer {token}"}
        )
        return response.status_code == 200
    # Similar checks for other services

Query interface:

def get_credential(service, project=None):
    # Returns the token from SQLite
    # Other agents call this instead of reading files

It's not fancy. But it works. We haven't lost a credential or had a false alarm since deploying it.

Bottom Line

If you're running more than 5 API integrations, you probably have credential sprawl. It starts small — a few env vars, a config file, some keys in your agent's memory. Then it grows.

By day 20, you're hunting through files trying to figure out which OpenAI key goes with which project. By day 60, your agent is giving false alarms because context compression ate its credential list. By day 100, something breaks in production because a token expired and nobody noticed.

Build the vault early. Make it the single source of truth. Add health checks so you catch problems before they break things. Let your agents query it instead of maintaining their own credential lists.

Your future self — and your agents — will thank you.

Build Your Own Agent Infrastructure

AutoClaw Agents is our framework for building specialized AI agent ecosystems. The Credential Vault Agent is one piece. We also have agents for content generation, social media management, trading signals, and more.

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