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Products that do what DCP does

Give your AI agents encrypted permission and keys

  1. 1

    Let AI agents run your next deal, fundraise or data room

    Jun 2026

  2. 2

    Give AI access to 6754+ APIs with zero credentials exposed

    Feb 2026

  3. 3
    Cred97

    OAuth credential delegation for AI agents

    Apr 2026

  4. 4
    Latchkey122

    Credential layer for local AI agents

    Mar 2026

  5. 5

    Give AI agents identity, secrets vault & analytics

    Feb 2026

  6. 6
    Astra116

    Make AI agents that never see your data

    Apr 2026

  7. 7
    Loomal92

    Identity infrastructure for AI agents

    Apr 2026

  8. 8

    Give your AI coding agent the web as a command line

    Jun 2026

  9. 9

    Data APIs for AI agents & developers — free to start

    Feb 2026

  10. 10IB

    Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…

    Jan 2026 · github.com

  11. 11AA

    Hey HN - I'm Mason, and I'm excited to share AgentCash - a CLI to help your agent discover and pay for premium APIs and paywalled data. The problem we kept running into was simple: if you want an agent to use premium data or services, the setup flow is awful. You have to find the right provider, sign up manually, subscribe, generate an API key, install tooling, and then teach your agent how to use it. Then do that again for the next provider. We wanted a simpler model: give the agent a universal balance, let it discover available resources, and let it pay per call. So AgentCash gives agents…

    Mar 2026 · agentcash.dev

  12. 12CS

    AI agents are starting to get real access like GitHub tokens, cloud credentials, customer data, deploy permissions. Not coincidentally, the rate of major cybersecurity incidents is rising rapidly. See for yourself: https://epoch.ai/data/cve?view=graph https://genai.owasp.org/resource/state-of-agentic-ai-securit... My friend and I, both AI researchers, are working on fixing this through an open-source project we've just started called Clay Seal. We've started with a simple version of Identity: an open-source way to issue short-lived, verifiable…

    Jul 2026 · github.com

  13. 13MA

    Show HN: SEKSBot – AI agents that can't see your secrets SEKSBot is a fork of OpenClaw where agents have zero access to API keys, tokens, or credentials — ever. The core insight is borrowed from SQL prepared statements: separate the instructions from the sensitive data. Agents write requests using named secret references. A broker intercepts and injects the real credentials at execution time. The agent never sees them. How it works: seksh (our nushell fork) has secure built-in commands (seksh-http, seksh-git) that route through the broker. Agents can make authenticated API calls and git…

    Feb 2026 · seksbot.com

  14. 14

    Scam-proof your AI agents

    3d ago · agentlooker.ai

  15. 15PA

    We built PrivateClaw because the hosted OpenClaw platforms on the market today require you to trust them with plaintext. PrivateClaw removes that requirement at the hardware layer. PrivateClaw runs AI agents inside Trusted Execution Environments (TEEs), backed by AMD’s SEV-SNP standard. This means that your data is encrypted at the hardware level, enforced by the AMD Secure Processor outside the host OS trust boundary. PrivateClaw comes with inference that also runs inside TEEs, which means your prompts and completions are private as well. How it works: Each user gets a dedicated CVM…

    Apr 2026 · privateclaw.dev

  16. 16AR

    Hi HN. I'm the founder of Phoenix Labs (ex TikTok, Applied AI) and we're open sourcing our internal tooling today which is like a toolchain / meta-harness for CLI agents useful for really scaling eng and creative work. We are a very small team who's building a very ambitious product so we had to find ways to squeeze every ounce of efficiency that we could get our hands on. Harness strengths of different models (Claude, GPTs) and CLI-harnesses (Claude Code, Codex), safe/robust browser integration to speed up UX/QA testing, teams cli to speed up security reviews and parallelize…

    May 2026 · agents-cli.sh

  17. 17VA

    Vincent lets users safely grant apps/agents limited, revocable permission to use their wallets. Think “OAuth for crypto actions”: you define scopes (e.g., “rebalance stables on Aave up to $1k/day”), users approve, and your app runs within on-chain guardrails. Non-custodial. Built with Lit Protocol's decentralized programmable signing.

    Oct 2025 · docs.heyvincent.ai

  18. 18AL

    AGENTS.lock keeps AI agent skills, instructions, and MCP servers in sync across Claude, Codex, Gemini, and Copilot CLIs using a single TOML lockfile as the source of truth. Instead of manually copying skills and configs between tools, you declare everything once in AGENTS.lock and run `al sync`. GitHub: https://github.com/luml-ai/AGENTS.lock

    Jan 2026 · github.com

  19. 19AS

    MachineAuth is a self-hosted OAuth 2.0 server for authenticating AI agents and machines. What is an AI agent in this context? A software bot (like OpenCLAW, Claude Code, etc.) that makes API calls to access protected resources. Instead of sharing long-lived API keys, your agents can authenticate using OAuth 2.0 Client Credentials and receive short-lived JWT tokens. Why? No more sharing API keys Short-lived tokens (configurable) Easy credential rotation Industry-standard security

    Feb 2026 · github.com

  20. 20KD

    Every AI agent that does something useful - opening a PR, posting in Slack, updating a ticket - needs to call an API on behalf of a user. That means OAuth. Authorization flows, token storage, refresh logic, per-user credential isolation. Today, most teams solve this with a long-lived API key in an .env file, shared across every user and every session. As everyone in an organization becomes a software engineer - whether they know it or not - you can't expect each of them to roll their own OAuth. Secure credential handling needs to be baked into the infrastructure. The core issue: agents are a…

    Mar 2026 · kontext.dev

  21. 21OS

    Hi HN, Matvey, Ildar, Joey, and Dominik here. If you're building LLM agents that use tools, you're probably worried about prompt injection attacks that can hijack those tools. We were too, and found that solutions like prompt-based filtering or secondary "guard" LLMs can be unreliable. Our thesis is that agent security should be handled at the network level between the agent and the LLM, just like a traditional web application firewall. So we built Archestra Platform: an open-source gateway that acts as a secure proxy for your AI agents. It's designed to be a deterministic firewall against…

    Oct 2025 · archestra.ai

  22. 22OS

    Hello, my name is Andrei. My friends and I recently built CentralMind Getaway, an open-source tool that automatically generates AI-agent-optimized APIs from your database connection. It’s designed for those who don’t want to expose direct SQL access to their databases and prefer not to spend time building these APIs manually. What it does: - Auto-generates APIs from your database connection, infer schema & sample data using AI - Filters out PII and sensitive data for compliance (GDPR, SOC 2, etc.) - Optimized for AI-Agent with extra meta information and REST and MCP protocol support -…

    2025 · github.com

  23. 23

    Verify agent payment endpoints before your AI spends

    Aug 2026

  24. 24IM

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