MoorAI vs Enkrypt AI
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Enkrypt AI sells guardrails as a service for agents, apps and MCP, and coding agents are one of the places it reaches. MoorAI is built for coding agents and decides on the device. Enkrypt describes its runtime product this way: “Enkrypt AI Guardrails is the runtime layer that approves, modifies, or blocks risky behavior across agents, tools, RAG, and MCP - with decisions you can audit.” (enkryptai.com/product/agent-guardrails) For coding agents it says “Guardrails integrate via hooks or proxy.” and lists “Works with Cursor • Claude Code • Kiro • CrewAI • LangGraph • OpenAI SDK • Vercel AI”. (enkryptai.com/solutions/secure-vibe-coding) MoorAI is a PreToolUse hook inside the coding agent and an MCP stdio proxy in front of the tool servers. It reads the prompt, the file read into context, the shell command and the Model Context Protocol (MCP) arguments and results, and coaches, masks or blocks on what it finds.
The difference that matters most is where content is judged. Enkrypt’s coding-agent page says: “Command allowlisting and file access policies are evaluated locally in microseconds. More complex policies that involve content inspection add single-digit milliseconds.” (enkryptai.com/solutions/secure-vibe-coding) It does not say where that content inspection runs. Its open-source MCP Gateway runs guardrails with an Enkrypt key: “We also use Enkrypt API Key if you want to protect your MCPs with Enkrypt Guardrails.” (github.com/enkryptai/secure-mcp-gateway) “VPC / On-prem deployment” is listed on its Enterprise plan. (enkryptai.com/pricing) MoorAI decides against a 77-threat matrix on the machine and by default sends only category · risk · keyed one-way hash.
Enkrypt covers far more ground than the coding agent, and it now belongs to Anaconda. Anaconda “today announced it has acquired Enkrypt AI” on 4 August 2026 and states that “Enkrypt AI remains available today with no changes to existing products, plans, or support for current users.” (anaconda.com press release) Beyond coding agents, Enkrypt red-teams models and agents, guards customer-facing apps across text, vision and audio, scans MCP servers as a service, publishes a model safety leaderboard, turns regulations into controls and protects OpenClaw agents. Most of that is outside MoorAI’s scope. The rows where Enkrypt covers more ground are further down.
Three things this page does not state. (1) Which hook events Enkrypt’s coding-agent guardrails use. Its page says hooks or proxy, and its code sample says “via API wrapper, proxy, or SDK”. We found no coding-agent hook guide in its documentation index, so per-agent mechanics are marked unconfirmed. (2) Where content inspection runs on the coding-agent path. Local evaluation is stated only for command allowlists and file access policies. (3) What the acquisition changes. Anaconda says details are to be shared “as they become available”. Every Enkrypt statement below is quoted from Enkrypt’s or Anaconda’s own pages or from Enkrypt’s GitHub repositories, and the page is named.
Both decide on what an action contains. They differ on where the deciding happens and on how much of the agent’s traffic each one sees.
curl, wget, nc, ssh, package installs), files to block (~/.ssh/*, .env, *.pem) and actions that need approval (deploy, push, rm -rf). (enkryptai.com/solutions/secure-vibe-coding) MoorAI stops the same credential reads and uploads, and adds checks Enkrypt’s pages do not describe: a risky action aimed at something the user’s own request never named (intent alignment), a near-miss package name before npm or pip installs it, a proxy plus a CA override that lets traffic be read in transit, the agent’s rules files leaving the device, and a local secret value leaving even when it does not look like a token.Where MoorAI holds ground Enkrypt AI does not
These rows follow from running inside the coding agent’s own hooks and deciding on the machine. Several Enkrypt marks are unconfirmed rather than absent, because Enkrypt does not document its coding-agent integration in detail.
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| MoorAI | Enkrypt AI | |
|---|---|---|
| Content inspection runs on the device, with no vendor service in the decision | ✓on-device threat matrix | ◐allowlists and file policies run locally; content inspection site not stated |
| By default only category · risk · keyed one-way hash leave the device | ✓capture tiers are opt-in, admin-enabled | —decisions logged with policy_id and reason_code; contents of the record not public |
| Documented per-agent hook install for Claude Code, Codex CLI, Copilot CLI, Gemini CLI and Cursor | ✓validated end to end on Claude Code; the other four not yet against the live agents | —names Cursor, Claude Code and Kiro; mechanism not documented |
| Scans what comes back into the agent from shell commands, fetched pages and sub-agents | ✓PostToolUse, 64 KB window, Claude Code | ◐MCP Gateway validates MCP tool responses |
| Flags a risky action aimed at something the user’s request never named | ✓intent alignment; lexical, keyed hashes | — |
| Stops a typosquatted or hallucinated package name at install | ✓slopsquatting gate, name only, offline | —sample policy blocks package installs outright |
| Reports a proxy plus CA override that lets an agent’s traffic be read in transit | ✓transit-override detection (#67) | — |
| Reports the agent’s rules files (CLAUDE.md, AGENTS.md) leaving the device | ✓keyed shingle fingerprints, no text stored | — |
| The enforcement point is open source, so the data claim can be checked in code | ✓agent MIT | ◐MCP Gateway and Skill Sentinel Apache-2.0; other Enkrypt software proprietary |
| Coaches with no account; enforces free up to 200 users | ✓agent free; console free to 200 users | ◐free tier with 50 credits a month; paid plans from $149 a month |
Where Enkrypt AI covers ground MoorAI does not
This list is longer. Enkrypt secures models, apps, agents and MCP servers across an enterprise, and now ships inside the Anaconda Platform. MoorAI governs what coding agents do on endpoints and in server mode.
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| MoorAI | Enkrypt AI | |
|---|---|---|
| Red teaming of models, apps and agents as a product, including multimodal | ◐moorai-redteam runs a corpus against your own policy | ✓ |
| Guardrails for customer-facing apps and RAG, across text, vision and audio | ✗ | ✓"Policies apply to text, vision, and audio" |
| A public safety leaderboard of 200+ models | ✗ | ✓ |
| Regulations turned into enforced controls (NIST AI RMF, EU AI Act) | ◐moorai-compliance maps signals to controls; no policy generation | ✓ |
| Hosted scanning of MCP servers from a GitHub repo, npm package or remote endpoint | ◐moorai-scan analyses packages and repos on your machine; no hosted service | ✓MCP Scanner |
| MCP servers launched in an isolated sandbox (Docker, Podman, microVMs) | ✗the proxy enforces; it does not sandbox | ✓MCP Gateway |
| Runtime protection for OpenClaw agents | ✗ | ✓ClawPatrol plugin |
| Skill scanning with VirusTotal lookups for binaries and archives | ◐Skill Analysis and moorai-scan; no malware-database lookup | ✓Skill Sentinel |
| Distribution through a data-science platform, and an OpenAI compliance partnership for ChatGPT Enterprise | ✗ | ✓Anaconda Platform |
Same capability, different mechanism
Both products do each of these, so the table describes how rather than scoring.
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| MoorAI does it by… | Enkrypt AI does it by… | |
|---|---|---|
| Stopping a coding agent’s action before it runs | A PreToolUse hook in the agent’s own process, validated end to end on Claude Code. Codex CLI, Copilot CLI, Gemini CLI and Cursor block through their own pre-tool hooks and are not yet validated against the live agents. Server mode runs the same hook for claude -p in CI, containers and Agent SDK services; one live claude -p run is proven, and an Agent SDK service and a GitHub Actions run have not been watched end to end. |
Guardrails that “Hook into your coding agent’s execution path and enforce policy in real time”, integrated “via hooks or proxy”, with a policy pack of blocked commands, blocked files and approval-required actions. (enkryptai.com/solutions/secure-vibe-coding) |
| Enforcing on MCP tool calls | An MCP stdio proxy on the device that scans arguments and results and refuses a blocked call before the real server sees it, for any host that launches a stdio MCP server. | An open-source gateway that “sits inline between agents and MCP servers to approve, modify, or block tool calls” (enkryptai.com/product/mcp-gateway), added to Claude Code with secure-mcp-gateway install --client claude-code, with guardrails applied through an Enkrypt API key. (github.com/enkryptai/secure-mcp-gateway) |
| Vetting skills before an agent loads them | Skill Analysis labels every skill, subagent, command, MCP config and hook-bearing settings file by intent and keeps a drift fingerprint, attaching no text. moorai-scan gives a content-free verdict before install. |
Skill Sentinel, which “uses multi-agent AI analysis to detect prompt injection, data exfiltration, command injection, malware, and other threats hiding in skill packages for Cursor, Claude Code, Codex, and OpenClaw.” (github.com/enkryptai/skill-sentinel) It calls a language model, local or hosted. |
| Evidence of a decision | A signed, content-free decision receipt per verdict (tool, category, risk, decision and one-way hashes, signed with ed25519) and a hash-chained on-device log. | A decision record where “Every decision includes policy_id, policy_version, and reason_code”. (enkryptai.com/product/agent-guardrails) Whether the record carries content is not stated. |
MITRE ATLAS, as documented. In our reading of vendor material against the 76 ATLAS techniques tagged Agentic AI, Enkrypt AI’s published material documents 20 of the 76 (read 1 October 2026), 8 of them with a limit the vendor states. Several of the 20 come from blog posts and from red teaming rather than from the coding-agent product, and the MCP Gateway enforces only where MCP traffic is routed through it. That counts what the documentation says, not a test of the product. The method and every quote behind the number are in What vendors actually document against MITRE ATLAS.
Where MoorAI is stronger. Content judged on the machine, at the coding agent’s own hooks. The file read, the shell command, the MCP argument and result, the prompt and the output are read on the device and coached, masked or blocked there, with a documented install for five coding agents and checks Enkrypt does not describe: intent alignment, typosquatted packages, transit overrides and rules-file leaks. The console receives no content, the code that guarantees that is MIT, and it is free to enforce up to 200 users.
Where Enkrypt AI is stronger. Breadth across the AI estate. Red teaming of models and agents, guardrails for customer-facing apps and RAG across text, vision and audio, a public leaderboard of 200+ models, regulations turned into enforced controls, hosted MCP server scanning, an open-source MCP gateway that can sandbox the servers it fronts, Skill Sentinel with VirusTotal lookups, and OpenClaw protection. It publishes its prices, with a free tier and paid plans from $149 a month, and it now ships through the Anaconda Platform, whose release also names Enkrypt an OpenAI compliance integration partner. If the job is securing AI apps and models across an enterprise, Enkrypt is the larger product and MoorAI is not one.
Which to run where. Run Enkrypt where models, customer-facing apps and RAG need guardrails and red teaming, where MCP servers need scanning before adoption, or where Anaconda is already the platform. Run MoorAI on developer machines and in CI where the question is what a coding agent is about to read, run or send, and where the record should hold no prompt content. Both can sit in front of MCP servers; nothing in either’s public material says they conflict on one machine, and we have not run them together.
Questions about MoorAI and Enkrypt AI
How does Enkrypt AI connect to Claude Code and Cursor?
Enkrypt says its guardrails integrate via hooks or proxy, and it lists Cursor, Claude Code and Kiro among the agents it works with. Its open-source MCP Gateway is added to Claude Code as an MCP server with secure-mcp-gateway install --client claude-code. We found no per-agent hook guide in its documentation index. MoorAI installs a PreToolUse hook in Claude Code and pre-tool hooks in Codex CLI, Copilot CLI, Gemini CLI and Cursor.
Does Enkrypt AI inspect content on the developer’s machine?
Partly, per Enkrypt: command allowlisting and file access policies are evaluated locally, and policies that involve content inspection add single-digit milliseconds, without saying where that inspection runs. Guardrails in its MCP Gateway use an Enkrypt API key, and VPC or on-prem deployment is on its Enterprise plan. MoorAI runs detection on the device and sends a category, a risk level and a keyed one-way hash by default.
Who owns Enkrypt AI?
Anaconda announced on 4 August 2026 that it has acquired Enkrypt AI. Anaconda states that Enkrypt AI remains available with no changes to existing products, plans or support for current users, and that further details will be shared as they become available.
Is Enkrypt AI open source?
Parts of it. The MCP Gateway and the Skill Sentinel scanner are published on GitHub under Apache-2.0, and the gateway’s README says other Enkrypt AI software is under a proprietary licence. The MoorAI agent is MIT; the MoorAI console is source-available under the Elastic License 2.0 and free up to 200 users.
Does MoorAI replace Enkrypt AI, or the other way round?
No. Enkrypt secures models, apps, agents and MCP servers with red teaming, guardrails and scanning, most of which MoorAI does not attempt. MoorAI inspects what a coding agent’s actions contain and coaches, masks or blocks on the device. They overlap at the coding agent and differ on where content is judged.
Enkrypt AI capabilities are taken from Enkrypt’s and Anaconda’s own published material, checked on 1 October 2026: Secure Vibe Coding, Agent Guardrails, MCP Gateway, MCP Scanner, ClawPatrol, enkryptai.com/pricing, github.com/enkryptai/secure-mcp-gateway, github.com/enkryptai/skill-sentinel and Anaconda’s acquisition announcement. Every quoted phrase is Enkrypt’s or Anaconda’s. ◐ = partial: present but narrower than the other column. — = unconfirmed, not necessarily absent. MoorAI marks reflect shipped capability: hook enforcement is validated end to end on Claude Code; Codex, Copilot CLI, Gemini CLI and Cursor block through their own pre-tool hooks and are not yet validated against the live agents. The agent is MIT and runs on macOS, Windows and Linux; the console is source-available under the Elastic License 2.0 and free up to 200 users. Enkrypt AI is a trademark of its owner; this page is independent and is not affiliated with or endorsed by Enkrypt AI. Both products change, so check specifics against current documentation.