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PopNx MCPMCP servers for people who use AI · explained in plain words

Actenon Kernel

by Actenonversion 1.2.2i★ 2iRuns on your computer
Registry nameio.github.Actenon/kernel

How to install

Overview

Description from the maker (original English)

Verify consequential AI actions before they execute.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Passed 3/3 checks · Runs on your computer

First: which AI do you use?

Pick your app and the steps appear below.

Works with Claude, with some setup first

Install Python (uv) on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone

  1. Install Python (uv)

    One time only; it works for every server that needs Python (uv)

    Open the Python (uv) download page ↗

  2. Open the Claude desktop app’s settings file

    SettingsDeveloperEdit Config

  3. Paste these settings and save the file

    {
      "mcpServers": {
        "kernel": {
          "command": "uvx",
          "args": [
            "actenon-kernel",
            "--demo"
          ]
        }
      }
    }
  4. Quit Claude and open it again

  5. Try it

    Use Actenon Kernel and tell me what you can do for me, then show me one thing

    ✓ If Claude says it is using Actenon Kernel or shows a Actenon Kernel tool in the answer, you are connected

Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version

ChatGPT cannot connect Actenon Kernel yet

Actenon Kernel runs on your computer, but ChatGPT can only connect servers that run on the web

What you can do instead

A · Use an app that can connect Actenon Kernel

  • Install Python (uv) on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone
  • Install Python (uv) on your computer first (one time)
  • Install Python (uv) on your computer first (one time)
  • Install Python (uv) on your computer first (one time)

B · Others in Other that work with ChatGPT

Picked from the most used in the same category, only ones that connect by address with no key

Works with Claude Code, with some setup first

Install Python (uv) on your computer first (one time)

  1. Install Python (uv)

    One time only; it works for every server that needs Python (uv)

    Open the Python (uv) download page ↗

  2. Open Terminal

    Mac: press Command+Space and type Terminal · Windows: open PowerShell

  3. Paste this command and press Enter

    claude mcp add kernel -- uvx actenon-kernel --demo
  4. Type /mcp in Claude Code

    You should see Actenon Kernel listed as connected

  5. Try it

    Use Actenon Kernel and tell me what you can do for me, then show me one thing

    ✓ If Claude Code says it is using Actenon Kernel or shows a Actenon Kernel tool in the answer, you are connected

Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with Cursor, with some setup first

Install Python (uv) on your computer first (one time)

  1. Install Python (uv)

    One time only; it works for every server that needs Python (uv)

    Open the Python (uv) download page ↗

  2. Click this button to open Cursor

    Open in Cursor

    Cursor asks you to confirm; click Install

  3. Open the AI chat in Cursor in Agent mode

  4. Try it

    Use Actenon Kernel and tell me what you can do for me, then show me one thing

    ✓ If Cursor says it is using Actenon Kernel or shows a Actenon Kernel tool in the answer, you are connected

Menu names checked against Cursor’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with VS Code, with some setup first

Install Python (uv) on your computer first (one time)

  1. Install Python (uv)

    One time only; it works for every server that needs Python (uv)

    Open the Python (uv) download page ↗

  2. Click this button to open VS Code

    Open in VS Code

    VS Code asks you to confirm; click Install

  3. Open the AI chat in VS Code in Agent mode

  4. Try it

    Use Actenon Kernel and tell me what you can do for me, then show me one thing

    ✓ If VS Code says it is using Actenon Kernel or shows a Actenon Kernel tool in the answer, you are connected

Menu names checked against VS Code’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Other apps that use MCP, such as Windsurf, Zed or Gemini CLI, each add servers differently. See how in the app list.

See every app that uses MCP →

JSON settings are under “For developers” below

Stuck? Ask people who use Actenon Kernel💬 Discussion →
For developers: Terminal commands and JSON settings

Installed on your computer

Claude Code

claude mcp add kernel -- uvx actenon-kernel --demo

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "kernel": {
      "command": "uvx",
      "args": [
        "actenon-kernel",
        "--demo"
      ]
    }
  }
}

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "kernel": {
      "command": "uvx",
      "args": [
        "actenon-kernel",
        "--demo"
      ]
    }
  }
}

VS Code (mcp.json)

{
  "servers": {
    "kernel": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "actenon-kernel",
        "--demo"
      ]
    }
  }
}

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

At a glance

Downloads per weeki
210/wk
Licencei
Apache-2.0
Connection
Runs on your computer
Latest versioni
1.2.2
Categoryi
Other
Published to registryi
Jul 25, 2026
Code last changedi
Nov 3, 2026
Maker
Actenon
Packages
pypi: actenon-kernel
Website
github.com
Registry status
Active

Which apps can use it

Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.

Run on your computer in

ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast

All apps, with pros and cons →

Related guides

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 11, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account Actenon, which owns the repo

  • ✓ Pass

    Still maintained

    Code last changed 9 days ago

  • ✓ Pass

    Has a licence

    Uses Apache-2.0

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Discussion

Ask, share a tip or report that it does not work. Sorted by what people marked helpful.

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Posts here are written by users, not the PopNx team.

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User reviews

No reviews yet

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Compared with others in Otheri

  • More stars than 91% of the other 19237 servers in this category
  • Published to the registry more recently than 16% of the other 19237 servers in this category
  • Basic checks equal to or better than 100% of the other 19237 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Actenon Kernel safe?

It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed 9 days ago, and the latest version (1.2.2) reached the registry 4 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: World Monitor, Claude Flow, Tldraw

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

World Monitor

Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 102 tools.

by koala73Widely used★ 90.5KUpdated 6 days ago

Runs in the cloud✓ worldmonitor.app

Claude Flow

AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.

by ruvnetWidely used↓ 13.5K/wk★ 81.5KUpdated 14 months ago

Runs on your computer

Tldraw

Draw and visually collaborate with your agents on tldraw's canvas.

by tldrawWidely used★ 51.4KUpdated 8 months ago

Runs in the cloud

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Actenon Kernel

The open verifier for proof-bound consequential execution. Defines what a valid proof is. Verifies proofs at the execution edge; issues no grants; runs no policy decisions.

Every claim above is machine-verified

The claims: machine-verified badge links to a CI gate (verify-claims.yml) that fails on every PR, push to main, and once a day if any factual claim this README makes about the kernel stops being true:

  • Zero network calls during verification — tests/test_neutrality.py runs in the gate, not just behind a badge link.
  • Runs without Permit, Cloud, or Scan — tests/test_independence.py, plus a source scan proving the kernel never imports Cloud or Permit, plus scripts/assert_dep_direction.py (runtime deps are exactly actenon-protocol).
  • The conformance count — every "N conformance vectors" / "N tests pass" here is compared against what actenon-kernel conformance run actually executes; the vector files themselves are hash-locked by scripts/verify_conformance_manifest.py.
  • Install commands — every pip install in this README is resolved against the live registry; the Python badge is generated, not hand-edited.
  • The ecosystem table — rendered from the protocol's ecosystem.yaml, never hand-edited.

The Invariants workflow additionally proves on every PR that a clean, no-extras install verifies the full conformance surface — 33/33 tests, zero skips — including Ed25519.

If a claim drifts, the badge goes red before a human notices.


The Actenon ecosystem

The Kernel is one of the independent repositories that together close the execution gap — the gap between *upstream authorization* and the *execution edge* that actually performs a consequential side effect.

RepositoryRoleDepends onPackages
`actenon-protocol`The neutral wire contract — what every artefact looks like on the wire—actenon-protocol (PyPI) · @actenon/protocol-types (npm)
`actenon-kernel` ← you are hereThe open verifier — defines what a valid proof isactenon-protocolactenon-kernel (PyPI)
`actenon-permit`The developer on-ramp and authority brokeractenon-kernel, actenon-protocolactenon-permit (PyPI) · @actenon/sdk (npm)
`actenon-scan`The independent static-analysis scanner—actenon-scan (PyPI)
`sdk-go`Go verifier SDK — protected-endpoint proof verification in Goactenon-protocolrepo
`sdk-rust`Rust verifier SDK — protected-endpoint proof verification in Rustactenon-protocolrepo

Optional: actenon-cloud — a managed control plane (private repository, not publicly available). Not required by any component above; every capability in this ecosystem works without it.

Every repo can be adopted independently. The Kernel in particular can be wired in at the agent framework (LangChain tool, MCP tool, Claude Managed Agents custom tool, etc.) or independently at the resource boundary (FastAPI route, Express route, Go HTTP handler). Both placements are first-class.


What this is

The Kernel is the trust anchor of the Actenon ecosystem. It is:

  • Independent — runs without Permit, Cloud, or Scan. Zero network calls during verification.
  • The verifier at the execution edge — the PCCBVerifier is pure and stateless; the ProtectedExecutor enforces replay, escrow, idempotency, and credential brokering at the edge before any side effect, then emits the Receipt or Refusal.
  • Conformance-locked — 53 conformance vectors define exactly what "a valid PCCB" means, in any language.
  • Multi-language — Python reference, plus TypeScript, Go, and Rust verifier SDKs that all conform to the same vectors.
  • Framework-agnostic — proof verification is a function call, not a framework. The same verifier runs inside a LangChain _run, an MCP tool handler, an Express route, or a Go HTTP handler.

The Kernel does one thing: it verifies that a PCCB (Proof of Constrained Capability Bound) authorizes an exact Action Intent for this caller, this target, this audience, this scope, this time window, and this single execution attempt — and the ProtectedExecutor refuses the attempt (no side effect, structured Refusal emitted) if verification fails. The Kernel does not issue grants or make policy decisions — that's Permit's job.

Guarantee precondition: the edge guarantee holds when the protected edge is the only path to the resource, the backend accepts only brokered credentials issued after verification, and the agent has no standing credential or alternate route. If those conditions are not met, the Kernel still refuses invalid proofs — but it cannot prevent a caller that bypasses it from reaching the resource. Full scope in docs/SCOPE_AND_GUARANTEES.md.

Why it exists

Modern agent stacks already answer the upstream question — *should this requester be allowed to do this kind of thing?* — with authentication, policy engines, approval workflows, and audit logs. They still leave open the question the execution edge needs to answer:

Is the exact action about to execute still the exact action that was authorized — for this endpoint, this tenant, this subject, this target, and this time window?

That unanswered question is the execution gap. It is where parameter mutation between approval and execution, replay of valid-looking proof, presentation to the wrong endpoint, tenant/subject rebinding, and stale-proof reuse actually happen. The Kernel closes it.

Read the canonical problem statement in THE_EXECUTION_GAP.md.

The two places you can wire it in

This is the single most important architectural decision in any Actenon adoption, and the Kernel is explicitly designed for both placements.

Placement A — at the agent framework (brokered mode)

The Kernel verifier runs inside the agent's tool implementation. The agent calls a tool; the tool verifies proof; the tool executes. The agent never holds a production credential — the broker resolves it after verification.

agent → framework tool (LangChain / MCP / Claude / CrewAI / ...)

↓ verifies PCCB locally ↓ brokers credential ↓ executes side effect Receipt or Refusal

This is the path you take when you control the agent framework and want to bind every tool call to proof. See INTEGRATIONS.md for the six ranked framework paths.

Placement B — independently at the resource boundary (resource-owned mode)

The Kernel verifier runs inside the resource itself — a FastAPI route, an Express endpoint, a Go HTTP handler, an internal service method. The resource is the protected endpoint. The agent (or any caller) must present a valid PCCB to cause a side effect, regardless of how it got there.

any caller (agent / human / service / attacker)

↓ presents PCCB resource boundary (FastAPI / Express / Go / ...) ↓ verifies PCCB locally ↓ executes side effect Receipt or Refusal

This is the path you take when you cannot fully trust the agent framework, when the resource is shared by multiple callers, or when the resource team and the agent team are different organizations. See the Boundary Kit in actenon-permit and the BoundaryVerifier API in this repo. BoundaryVerifier verifies a signed PCCB against the exact Action Intent; it does not treat a token string as proof.

Both placements use the same Kernel, the same PCCB shape, the same conformance vectors, and the same Receipt/Refusal artefacts. You can mix them in one deployment.

The 15-step verification pipeline

PhaseStepsWhat's checked
A: Pre-auth1–5Structure, protocol version, canonicalisation, key resolution, signature
B: Post-auth6–13Time validity, audience, boundary, target, action, parameter digest, authority, revocation
C: Stateful14–15Replay (deferred to executor), execution eligibility

Pre-auth failures collapse to a single public-safe code PROOF_INVALID. Post-auth failures disclose the specific code (AUDIENCE_MISMATCH, ACTION_MISMATCH, REPLAY_DETECTED, etc.) only to trusted callers. This two-layer refusal model is part of the protocol — see actenon-protocol.

What the Kernel produces

ArtefactPurposeSpec
Action IntentThe public, typed, attributable request for a consequential actionspec/action-intent/SPEC.md
PCCBThe proof artifact a protected endpoint verifies before side effectsspec/pccb/SPEC.md
ReceiptThe canonical structured success outcomespec/receipt/SPEC.md
RefusalThe canonical structured blocked-execution outcomespec/refusal/SPEC.md
Outcome AttestationOptional Ed25519-signed envelope wrapping a Receipt or Refusal (v2alpha1)spec/outcome-attestation/SPEC.md
Receipt Counter-SignatureOptional third-party counter-sign on a Receiptspec/countersignature/SPEC.md
Transparency Log EntryOptional digest-based public anchorspec/transparency-log/SPEC.md
Issuer Status

Only the beginning is shown; read the rest in the repo