Moltline Govern

Audit MCP configs and skill files for over-broad scope and injection risk.

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What it can do

  • Audit Mcp Config: Audit an MCP server config for risk-ranked posture findings. FREE. Flags exposed machine credentials in the config, required inputs that aren't gated/optional, unpinned versions, ove
  • Scope Check: Score the blast radius of every tool in a permission manifest. FREE. Ranks each tool by capability risk (command exec > money/delete > file-write/messaging > read > network) and flags the
  • Audit Skill File: Audit an agent skill or instruction file before you trust it. FREE. Checks for governance smells: prompt-injection and guardrail-bypass phrasing, concealment instructions ('don't tel

What data it sees

Do you need an account

No: the server works without sign-in

Audit MCP configs and skill files for over-broad scope and injection risk. 6 of 8 tools free.

Part of Moltline Studio: 22 hosted MCP servers, 160 tools, 110 of them free — no account, no API key, no signup. Independently audited — MCPize Verified A.

Direct endpoint: https://mcp.moltlinestudio.com/govern

How to connect

How to connect Moltline Govern to Claude

The server address to paste into Claude settings:

https://moltline-govern--techdpr.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect Moltline Govern to ChatGPT

The server address to paste into ChatGPT settings:

https://moltline-govern--techdpr.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect Moltline Govern to Cursor

The server address to paste into Cursor settings:

https://moltline-govern--techdpr.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (8)

Raw names from tools/list. Only developers need these.

audit_mcp_configAudit an MCP server config for risk-ranked posture findings. FREE. Flags exposed machine credentials in the config, required inputs that aren't gated/optional, unpinned versions, over-broad env access, and dangerous auto-run flags. It never echoes any matched secret value back. Typical input {"config": "<mcpize.yaml, mcp.json, or a Claude/Cursor servers block>"} returns {"posture_score": 0-100, "verdict": "...", "findings": [{"line": N, "severity": 1-5, "issue": "...", "fix": "..."}], "note": "..."}. Use on a server configuration document. Not for a skill or instruction file (audit_skill_file) and not for untrusted content an agent is about to read (injection_scan). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
scope_checkScore the blast radius of every tool in a permission manifest. FREE. Ranks each tool by capability risk (command exec > money/delete > file-write/messaging > read > network) and flags the over-privileged ones that need approval gates. Typical input {"tools": "[\"run_shell\", \"read_docs\"]"} returns {"tools_scored": N, "high_risk_tools": N, "ranking": [{"tool": ..., "blast_radius": 0-5, "capabilities": [...]}], "recommendation": ["..."], "note": "..."}. Use on a permission manifest to rank tools by blast radius. Not for the configuration that mounts them (audit_mcp_config). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
audit_skill_fileAudit an agent skill or instruction file before you trust it. FREE. Checks for governance smells: prompt-injection and guardrail-bypass phrasing, concealment instructions ('don't tell the user'), exfiltration language, and exposed credential material. Typical input {"content": "<SKILL.md, system prompt, or tool description text>"} returns {"verdict": "reject — do not install" | "no governance red flags on a pattern pass", "findings": [{"severity": 1-5, "issue": "..."}], "note": "..."}. Use before trusting a skill or instruction file that came from outside your own repository. Not for arbitrary untrusted input at run time (injection_scan). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
injection_scanScan untrusted text for prompt-injection patterns before ingestion. FREE. Use on any web page, email, or document an agent is about to ingest to catch prompt-injection and data-exfiltration patterns before they reach the agent's context. Typical input {"text": "<untrusted content>"} returns {"injection_suspected": bool, "count": N, "hits": [{"line": N, "pattern": "...", "text": "<flagged line>"}], "note": "..."}. Not for reviewing a skill file you control (audit_skill_file), and a clean result is not a guarantee of safety - it reports pattern matches only. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
inventory_reportBuild a governance inventory with risk tiers from a raw agent list. FREE. Turns a list of agents / MCP servers / skills into an audit-ready summary with critical/elevated/standard tiers and unowned-agent flags. Typical input {"items": "[{\"name\": \"deploy-bot\", \"owner\": \"ana\"}]"} returns {"total": N, "tiers": {"critical": N, ...}, "unowned_agents": [...], "inventory": [{"name": ..., "owner": ..., "tier": ..., "orphaned": bool}], "reading": "...", "note": "..."}. Use to turn a raw agent list into risk tiers. Not for auditing any single agent in depth (audit_mcp_config, scope_check). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
governance_policyGenerate an audit-ready agent-governance policy for a fleet. PREMIUM (license). Covers inventory cadence, ownership rules, least-privilege approval gates, injection defense, logging/retention, and decommissioning triggers. Typical input {"fleet_context": "20 agents, 3 with shell access, one finance bot"} returns {"policy": ..., "sections": {...}, "context_note": ..., "audit_checklist": ["...", ...]}. Use when a fleet needs a written policy document. Not for assessing what the fleet currently does (inventory_report, audit_mcp_config). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
get_auditor_personaLoad the Governance Auditor persona for consistent fleet audits. PREMIUM (license). The persona is methodical, evidence-driven, and allergic to 'it's probably fine'. Takes no arguments. Returns {"persona": ..., "identity": ..., "rules": ["...", ...], "opening_move": "..."} ready to adopt as a system prompt. Use to keep repeated audits consistent in voice and rigor. Not for running an audit - the audit tools do that. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
agent_readiness_scanScore a public domain against 21 agent-readiness checks. FREE. Use when you need to know whether an autonomous agent can discover, read, use or pay a website - your own, or a vendor you are evaluating before recommending it. Typical input {"domain": "example.com"} returns {"score": 8, "total": 21, "grade": "F", "passed": [...], "failed": [{"title": "...", "detail": "...", "fix": "..."}], "report_url": "..."} where report_url is a permanent shareable page for the same result. Not for auditing an MCP client configuration (audit_mcp_config) and not for scanning text for injection (injection_scan) - this one reaches out over the network and fetches public URLs on a live domain. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "The readiness scanner is not reachable right now."}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.