Lintsure
Compliance readiness checks for code: EU AI Act, GDPR, SOC 2, ISO 27001. Local. Not legal advice.
Beschreibung vom Entwickler (englisches Original)
MCP compliance proxy between agent and tools: deterministic governance, fail-closed, audit trail.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"kcp-harness": {
"command": "npx",
"args": [
"-y",
"kcp-harness",
"serve"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add kcp-harness -- npx -y kcp-harness serveIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"kcp-harness": {
"command": "npx",
"args": [
"-y",
"kcp-harness",
"serve"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"kcp-harness": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"kcp-harness",
"serve"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 8. Nov. 2026
Der Registry-Name wurde über die Domain cantara.no bestätigt (die Registry prüft, wem die Domain gehört)
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.4.1) kam vor 4 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: Lintsure, Premium Data MCP Server, Patents Trademarks Ip MCP Server
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
Compliance readiness checks for code: EU AI Act, GDPR, SOC 2, ISO 27001. Local. Not legal advice.
Government contracts, business registration, FDA recalls and product-price data as agent tools.
Patent search, inventor search, patents-by-assignee and full patent detail as agent tools.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
Deterministic knowledge governance for any AI agent.
*Your agent can read every file in your project. Can it prove why it read what it read?*
KCP Harness is an MCP compliance proxy that sits between an AI coding agent and its tools. It intercepts knowledge-related calls, routes them through the kcp-agent deterministic planner (14-gate cascade, no LLM), and produces compliance artifacts — decision traces, audit logs, budget ledgers — as a side effect of normal agent operation.
The agent can't bypass governance because it only talks to the proxy's MCP interface. The proxy decides what knowledge is accessible, tracks spend, and logs every decision. Fail-closed: if the harness can't verify a request, the agent gets nothing.
Agent (Claude Code / Cursor / Copilot / Windsurf / Cline / Crush / OpenClaw / ...)
│ │ MCP tool call v ┌─────────────────────────────────────────────────────────┐ │ kcp-harness │ │ │ │ classify → govern (14 gates) → execute → audit │ │ │ │ Side outputs: │ │ · Decision traces (per-request, deterministic) │ │ · Audit log (append-only JSONL) │ │ · Budget ledger (itemized, ceiling-enforced) │ │ · Temporal drift (plan validity over time) │ │ · Approval tickets (named-human sign-off, durable) │ │ · Confidence verdicts (post-synthesis gate) │ └─────────────────────────────────────────────────────────┘ │ v Knowledge manifests (knowledge.yaml)
[Documentation →](https://cantara.github.io/kcp-harness/)
Enterprises need agents that are *defensible* — auditable, reproducible, budget-controlled, temporally pinned. Today's agents can't prove why they read what they read. The harness adds a compliance layer without replacing the agent.
| What you keep | What the harness adds |
|---|---|
| Your agent (Claude Code, Cursor, Copilot, ...) | Deterministic knowledge selection |
| Your workflow (coding, reviewing, shipping) | Decision traces (14 gates per unit) |
| Your tools (MCP servers, shell, browser) | Budget enforcement (ceiling, per-currency) |
| Temporal governance (drift detection) | |
| Append-only audit log | |
| Replay / cross-examination | |
| Human-approval gates (named reviewer + policy citation) | |
| Confidence gating (post-synthesis, route-to-human) |
You sell the compliance layer. The agents are pluggable.
npm install -g kcp-harness
Or use without installing:
npx kcp-harness --help
Pre-built binaries (no Node/Deno required) for Linux x64/arm64, macOS x64/arm64, and Windows x64 — grab them from a release. To build one yourself:
npm ci && npm run build
deno compile --allow-read --allow-env --allow-net --allow-run \ --node-modules-dir=auto --output kcp-harness dist/cli.js
kcp-harness init # creates harness.yaml
kcp-harness integrate claude-code # or: pi, cursor, copilot, windsurf, cline, continue, crush, openclaw
Your agent now routes knowledge access through the harness. Every decision is logged.
| Agent | Config | Integration |
|---|---|---|
| Claude Code | .mcp.json + PreToolUse hooks | kcp-harness integrate claude-code |
| Cursor | .cursor/mcp.json + .mdc rules | kcp-harness integrate cursor |
| GitHub Copilot | .vscode/mcp.json (uses "servers" key) | kcp-harness integrate copilot |
| Windsurf | global config + .windsurfrules | kcp-harness integrate windsurf |
| Cline | MCP settings + .clinerules | kcp-harness integrate cline |
| Continue | .continue/mcpServers/*.yaml | kcp-harness integrate continue |
| Crush | crush.json + PrepareStep | kcp-harness integrate crush |
| OpenClaw | openclaw.json + plugin hooks | kcp-harness integrate openclaw |
| Pi | .pi/mcp.json + project skills | kcp-harness integrate pi |
Each agent has its own MCP config format, rules file, and quirks. The integrate command handles them all — one governance layer, any agent.
Every tool call flows through a five-stage pipeline:
1. RECEIVE MCP JSON-RPC request from agent
The classifier examines each tool call and determines whether it targets governed knowledge. Read("docs/api.md") where docs/ is governed? Route through the planner. Read("package.json") where package.json isn't governed? Pass through. KCP tools (kcp_plan, kcp_load) are always governed.
Two automated modes, plus a human gate that outranks both:
kcp_plan first. The harness caches the approved plan. Subsequent reads are checked against the cached plan — no re-planning.kcp_plan.governance.approvals rule are held for a named reviewer (pending), no matter what the automated paths would decide. Tickets survive restarts and resolve via the kcp-harness approvals CLI (or any custom ApprovalProvider channel). Resolutions require a named reviewer *and* a policy citation.Every knowledge unit is evaluated through 14 deterministic gates, in order:
audience → not_for → temporal → deprecated → supersession → relevance →
skill_eligibility → attestation → payment → access → strict → max_units → money_budget → context_budget
A unit must pass all gates. The gate that blocks it is recorded in the decision trace. Same inputs → same plan. No model involved.
For the skill_eligibility gate's subject matter — governed kind: skill units — the authoring conventions, linter, and conformance vectors live in Cantara/kcp-skill.
Once connected, agents can use these governance tools:
| Tool | Description |
|---|---|
kcp_plan | Deterministic load plan — which units, in what order, which skipped and why |
kcp_load | Plan + load eligible unit content |
kcp_trace | Full 14-gate decision trace |
kcp_validate | Lint a knowledge.yaml |
harness_status | Current governance state |
harness_session | Approved plans + known units for this session |
harness_budget | Itemized spend tracking |
harness_temporal_check | Plan drift detection |
harness_approvals | Human-approval tickets (pending / approved / dismissed / expired) |
harness_assess | Confidence-gate a synthesized answer before acting on it |
Append-only JSONL. Every decision — governed or pass-through — is logged with sequence number, timestamp, tool, targets, and governance decision:
cat .kcp-harness/audit.jsonl | jq 'select(.governed == true)'
Append-only itemized spend tracking. Per-currency running totals. Ceiling enforcement — a load that would exceed the budget is rejected atomically (no partial loads).
Plans are registered with a temporal watcher. On subsequent calls, the watcher re-evaluates against the current time. If units have drifted (expired, newly valid), the harness emits a drift event. Long-running sessions stay honest.
Calls matching an approval rule open a durable ticket (pending_review → approved | dismissed | expired, plus used for a consumed one-shot grant). The ticket store survives restarts — sessions are ephemeral, human review is not. Every resolution records *who* approved, *when*, and *which policy* it satisfies — evidence generated at approval time, never reconstructed from logs.
An approval is a bounded grant, never a standing permission. It covers the session that opened the ticket, the exact tool and target, and the call's arguments digest — and it lapses. Each rule sets grant: once | session | (default session), always capped by governance.approvals.grant_max (default 24h). A call outside a valid grant is denied, audited as grant_denied (expired, wrong_session, used, ...) and opens a *new* ticket. A standing permission is a policy rule, not a click. A grant's window is measured from the store's own clock, not the reviewer-supplied reviewedAt; the first valid resolution of a ticket wins (a dismissed ticket cannot be re-approved by an appended line); with approvals.require_signed_resolutions signatures are verified on every read, not only in resolve(); and approvals.require_args_binding refuses grants from tickets not bound to the call's arguments. What the ticket store does *not* protect — write access to its directory — is stated in the Ticket store trust model. See Governance Model.
harness_assess runs kcp-agent's post-synthesis assess() over a synthesized answer before it may be acted on. The planner gates *loading*, grounding gates *asserting*, this gates *acting*. Below-threshold verdicts on routed configs open an approval ticket with the full verdict embedded as evidence.
# harness.yaml
version: "1.0"
governance: domains:
policy: fail_closed: true audit_all: true max_units: 5 budget: amount: 1.00 currency: USDC
confidence: # optional post-synthesis gate (harness_assess) threshold: 0.7 severity: critical route_to_role: account-owner
approvals: # optional human-approval gates provider: file rules:
require_args_binding: true # refuse grants not bound to the call's arguments (recommended)
audit: path: ".kcp-harness/audit.jsonl"
kcp-harness serve [--config harness.yaml] Start the MCP proxy
kcp-harness init Create a harness.yaml template kcp-harness check [--config harness.yaml] Validate configuration kcp-harness integrate [options] Generate agent integration files kcp-harness integrate --list List supported agents kcp-harness export [options] Export compliance evidence (SOC 2 / ISO 27001) kcp-harness dashboard [options] Launch the live compliance dashboard kcp-harness approvals list [--state s] List human-approval tickets kcp-harness approvals approve --reviewer --policy-ref kcp-harness approvals dismiss --reviewer -
Nur der Anfang wird gezeigt; den Rest findest du im Repo