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AC mcp-oauth

Add OAuth 2.0 PKCE authentication to a remote MCP server. Use this skill whenever the user wants to add authentication to an MCP server, protect MCP tools with OAuth, implement login flow for an MCP connector, add user auth to an MCP endpoint, or set up token-based access for MCP. Also triggers on: 'MCP OAuth', 'MCP authentication', 'withMcpAuth', 'MCP login flow', 'protect MCP endpoint', 'MCP token auth', 'dynamic client registration MCP', 'Claude connector OAuth'. Even if the user just says 'add auth to my MCP server' or 'my MCP server needs login', use this skill.

ClawHub Agent Skills author: Luca v1.0.0 MIT-0 3 files body ≈ 2 705 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

IntegrationAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
99
Quality 40%
85
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Secrets in code secret-password-literal SKILL.md:234
      Hard-coded password / key literal (may be an example)
      const accessToken = crypto.randomBytes(16).toString('hex');

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 54/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 70When it triggers. States when to use, but not when not to
    • 85Steps. 6 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2705 tokens
    • medium 2 test cases, all positive: not one "should refuse" or "should ask first"

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +3Description length 573: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 6 items
    • +4Has examples (10 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: suspicious
    This instruction-only OAuth skill is purpose-aligned, but its sample authentication flow is under-scoped for production use and could lead users to deploy weak OAuth protections.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026