Launched this week
DCP
Give your AI agents encrypted permission and keys
109 followers
Give your AI agents encrypted permission and keys
109 followers
Today, many agents read keys and sensitive info from dotenv files, configs, or memory. One bad prompt or compromised tool can drain your wallet, API bill, or private data. DCP makes agents safe for real work: your wallets and API keys stay encrypted on your own machine. Give each agent only the scopes it needs; it asks, you approve from Telegram or App. Daily budgets, logs, and instant revoke keep you in control. Open source, non-custodial, and works with Claude, Cursor, OpenClaw, and Hermes.
the harder question underneath this product is whether detecting AI use in a technical interview is actually the right goal. a senior engineer who knows how to use AI tools effectively might be more valuable than one who can whiteboard without them. curious if there's a way to configure what counts as unauthorized versus what's just how people actually work now
DCP
@ansari_adin Thanks Ansari, I think this may have been meant for another launch today, but I agree with the broader point that AI tools are becoming part of real workflows.
For DCP, we’re focused on the permission layer: how agents can safely use wallets, keys, and sensitive tools without directly holding secrets.
DCP
@lakshminath_dondeti
Exactly, that’s the core problem DCP is built around.
I don’t think agents should directly hold private keys. They should request an action, show the scope/amount/destination, and let the user approve or reject it.
If the agent makes the wrong decision, DCP gives you guardrails: budgets, approval limits, logs, and instant revoke. The agent can ask, but it should not have custody.
Congrats on the launch! One question, if we hit the daily cap does it pause and wait for next day or does it notify you?
DCP
@prateek_kumar28 Thanks Prateek, good question.
If the daily cap is reached, agent can’t continue under that budget. The user gets notified, and they can either raise the limit manually or wait for the next budget window.
The goal is that agents can automate work, but they should never silently exceed the permission you gave them.
Rizzle AI
Love seeing builders focus on secure AI systems early.
DCP
@nithin_raju1 Exactly. Agent security has to be designed early, not patched in later.
If agents are going to take real actions for us, permission and control need to be built in from the start.
Cleo
good luck, guys. let's support each other!
DCP
@rahimwws Thanks Rahim, appreciate it.
Good luck with Cleo too. Founder becoming the PM is a real pain, and the transparent memory/trust-levels piece feels important if an AI PM is going to actually run parts of a team.
Also feels like there could be an interesting DCP × Cleo angle at some point: as Cleo moves from observer to operator, DCP could act as the permission layer for sensitive actions, approvals, budgets, and audit logs.
Would be happy to compare notes after launch day.