プロトタイプ · プレビュー版:公式レジストリのすべてのサーバーを掲載し、30分ごとに同期しています。レビューとアカウント機能は今後のステップで始まります。
PopNx MCPAIを使う人のためのMCPサーバー · やさしい言葉で解説

Stunt Double

作者:stunt-doubleバージョン 1.17.0i★ –iクラウドで動く
レジストリ名io.stuntdouble/mcp-server

インストール

概要

作者による説明(英語の原文)

Deploy AI user personas to validate user journeys at scale. Find UX friction before real users do.

PopNx MCPの3つの柱

この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。

できること

このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。

  • 接続方法: クラウドで動く
  • トランスポート: Streamable HTTP
  • カテゴリ: 開発者ツール

インストール

使っているAIアプリを選んで、設定をコピーしてください。

インストールの前に

必要なもの

どのアプリを使っていますか?

上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。

ウェブ、デスクトップ、モバイルのClaudeで使えます:

  1. Settings → Connectors を開く
  2. Add custom connector を押す
  3. 下のアドレスを貼り付けて Add を押す
  4. サインインを求められたら、作者のサービスにサインインする
SettingsConnectors1+ Add2https://…3
https://app.stuntdouble.io/api/mcp

ターミナルでこれを実行します

claude mcp add --transport http stuntdouble https://app.stuntdouble.io/api/mcp

Cursorで開く

または、設定を自分でコピーする

プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます

{
  "mcpServers": {
    "stuntdouble": {
      "url": "https://app.stuntdouble.io/api/mcp"
    }
  }
}

ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。

VS Codeで開く

または、設定を自分でコピーする

プロジェクトの .vscode/mcp.json に貼り付けます

{
  "servers": {
    "stuntdouble": {
      "type": "http",
      "url": "https://app.stuntdouble.io/api/mcp"
    }
  }
}

ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。

ChatGPTがつなげるのは、インターネット上のサーバーだけです:

  1. ウェブ版のChatGPTを開き → Settings → Connectors (Apps)
  2. Create または Add を押す(プランによっては、先に Advanced で Developer mode をオンにする必要があります)
  3. 下のアドレスを貼り付け、名前を付けて保存する
  4. サインインを求められたら、作者のサービスにサインインする
SettingsConnectors1+ Create2https://…3
https://app.stuntdouble.io/api/mcp

メニューの名前は、プランや時期によって少し違うことがあります。

選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。

この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。

できること

ツールの名前と説明は、サーバーが2026年11月6日に返したそのままの内容です。書いたのは作者で、私たちではありません。プレーンテキストとして表示しています。

  • get_me

    Get the account this connection is acting as: id, email, name, timezone and where notifications reach them. Use `timezone` when creating a scheduled workflow rather than defaulting to UTC, and `id` to tell your own runs and feedback from a teammate's in lists that carry only user

  • list_workspaces

    List the workspaces you belong to, with your role in each. Call this first: almost every other tool needs a workspace_id from here.

  • get_workspace

    Get workspace details by ID or slug, including the admin-set controls that decide what runs in it may do. `settings` is a ceiling, never a grant: a network policy there applies on top of each worker's own, and a feature switched off there cannot be switched back on per project.

  • list_workspace_members

    List the members of a workspace with their role, name and join date. Use it to resolve the user ids that runs, feedback and assignments carry.

  • search

    Search everything in a workspace (projects, actors, checklists, interviews, automations, issues, goals, feedback, knowledge, insights, design reviews, resources, conversations) by name or content. Use it instead of listing and filtering, and before creating something that may alr

  • list_projects

    List the live projects in a workspace, most recently opened first. Call this after list_workspaces and match a target URL or product name against these before creating anything new.

  • get_project

    Get one project (the product tracked by checklists, workflows, interviews and feedback), including its URL, audience and product description. Archived projects read as not found.

  • create_project

    Create a project (a product to track with checklists, workflows, interviews and feedback). Call list_projects first and reuse a matching project rather than creating a duplicate.

  • list_project_mcp_servers

    List the third-party MCP servers attached to a project and the tools each allows. Configuration only: those tools are not callable here, but an actor in a run (checklist, interview, workflow) may call the allowed tools of servers whose in_force is true. Servers are registered and

  • list_workspace_guidelines

    List the workspace's whole library of standing rules (design system, tone of voice, brand, compliance, accessibility, shared knowledge), with how many projects hold each one. Read this before writing a rule: attaching one that already exists with `set_project_guideline` beats typ

  • add_workspace_guideline

    Add a standing rule to the workspace library. Call list_workspace_guidelines first so you do not add a near-duplicate. Attach it to the projects it applies to with `project_ids` here or `set_project_guideline` later, or set `apply_to_design_reviews` so every design review in the

  • update_workspace_guideline

    Update a rule in the workspace library, or switch it off. Every project holding it is held to the new wording, so prefer editing the shared rule over adding a near-duplicate. Pass only the fields to change; at least one is required.

  • remove_workspace_guideline

    Remove a rule from the workspace library permanently. This detaches it from every project holding it, so prefer `update_workspace_guideline` with `enabled: false` when the rule may come back.

  • list_project_guidelines

    List the standing rules this project is held to: the workspace library rules it has attached. Read these before writing checks, interview guides or design feedback for the project, and assert them as observable checks rather than restating them. `attachment_id` is this project's

  • add_project_guideline

    Add a standing rule and hold this project to it (a design-system rule, a tone-of-voice rule, a compliance obligation, or shared knowledge). Every checklist run, design review, interview and triage for the project is then held to it. The rule joins the workspace library, so check

  • set_project_guideline

    Attach a library rule to a project, detach it, or switch it off for this project alone. Attaching is how one workspace rule comes to hold for several projects without being retyped. `enabled: false` keeps the attachment but stands the rule down here, leaving every other project u

  • list_actors

    List active actors (persistent AI user personas) in a workspace, oldest first. Prefer reusing an existing actor over creating a new one; pass an id from here to get_actor, interviews and checklists.

  • get_actor

    Get an actor's details: description, system prompt, capabilities, and status. list_actor_knowledge has the knowledge it carries into runs.

  • create_actor

    Create an actor: a persistent AI user persona with its own browser, email inbox (for OTP and magic-link flows), and memory. The description shapes who the persona is, so describe a person (background, goals, tech comfort), not a job title. Call list_actors first and reuse a match

  • update_actor

    Update an actor's name, description, system prompt, capabilities, or status. Only the fields you pass change; at least one is required. Set status to "archived" to soft-delete.

  • list_actor_knowledge

    List what an actor knows, oldest first. Each entry has a kind: expertise and process entries are listed by title in every run and the actor reads one when the task calls for it; reference and account entries are found by search. Check here before add_actor_knowledge to avoid dupl

  • add_actor_knowledge

    Add knowledge to an actor. Choose the kind: expertise for a skill or standard it judges by in every run (brand, tone of voice, design system, compliance, accessibility), process for steps it follows, reference for facts it looks up when relevant (product docs, FAQs, policies), ac

  • remove_actor_knowledge

    Remove a knowledge entry from an actor permanently, so future runs no longer use it. Find the entry's id with list_actor_knowledge.

  • list_conversations

    List chat conversations with actors in a workspace, most recently active first, optionally filtered to one actor. Excludes the workspace assistant's conversations. Pass an id to get_conversation to read the messages.

  • get_conversation

    Get an actor conversation with its full message history, oldest message first. Find conversation ids with list_conversations.

  • list_checklists

    List the checklists in a workspace, with their target URL, actor, check count and a recent run. Check here before creating a new checklist: re-running an existing one keeps its history as a regression signal. Use get_checklist for the checks themselves.

  • get_checklist

    Get a checklist: its target URL, instructions, run settings, every check (with the `id` update_checklist needs to edit one in place) and its 10 most recent runs. Call get_checklist_run with a run id for per-check results and evidence.

  • get_checklist_run

    Get a checklist run: per-check results with evidence, score, verdict and the change since the previous run. Poll after run_checklist every 30 to 60 seconds until `status` is terminal; `outcome` is the verdict on the experience. `comparison.changes` (what got better or worse) is u

  • flag_check_verdict

    Correct a wrong passed or failed verdict on one check: pass the result_id from get_checklist_run and a note on what was actually true. Later runs use it as calibration and re-record any code-run script; the run's own score is unchanged. Set clear to withdraw a correction.

  • run_checklist

    Run a checklist (async): the actor drives a real browser through the product and judges each check, and may use the project's attached MCP servers (list_project_mcp_servers). Returns a run_id; poll get_checklist_run (runs take a few minutes). Counts against the workspace's plan a

  • create_checklist

    Create a browser checklist: an actor exercises the product at a URL and judges each check with evidence. Checks can verify flows ("a new user can complete signup") or assert standards ("headlines use sentence case"), for brand, compliance and design-system audits. Any reachable U

  • update_checklist

    Update a checklist. Only the fields you pass change. Pass `checks` to replace the full set of checks, sending each existing check with the `id` from get_checklist so it keeps its run history. Changing the checks, instructions or url retires the recorded script, so the next run dr

  • delete_checklist

    Delete a checklist and its checks and runs. This permanently discards run history; prefer update_checklist, or simply not running a checklist, unless the user asks for deletion.

  • list_feedback

    List the comments stakeholders and users have left on a project through the feedback widget, newest first. Each one is pinned to a page position (often to a named element) and carries device info; filter by status "new" when triaging. Use summarise_feedback to turn a list of thes

  • get_feedback

    Get one feedback widget comment with its full reply thread, its page location and version, and a signed screenshot URL when one was captured. Find the id with list_feedback.

  • summarise_feedback

    Summarise a project's comments into themes ranked by severity, open questions, and a self-contained implementation brief for a coding agent. Read the brief before proposing changes instead of reasoning over raw comments. The brief leaves out work an open question holds up; `answe

  • update_feedback_status

    Update a feedback widget comment's status: "reviewed" once assessed, "resolved" when confirmed fixed (ideally after a checklist run proves it), "dismissed" sparingly. The dashboard reflects the change immediately.

  • list_workflows

    List workflows (multi-step automations) in a workspace, newest first, with their triggers, whether each is active, its step count and its last run. Call get_workflow on one for its steps and the order a run takes them.

  • get_workflow

    Get a workflow with its steps, the edges connecting them, the order a run would reach them, and recent runs. Read this before editing steps: `execution_order` is what actually runs, and any id in `unreachable_step_ids` is a step no run will ever reach.

  • run_workflow

    Trigger a workflow run now (async), whatever its trigger type: it executes the stored steps (see get_workflow), which can drive browsers, post PR comments and notify members. Returns a run ID; poll get_workflow_run. Refused over the plan limit or budget cap.

  • get_workflow_run

    Get a workflow run with step-level details. Poll this after run_workflow until status is terminal (completed, failed or cancelled).

  • create_workflow

    Create a workflow (multi-step automation) that runs checks without anyone asking. Triggers: manual, schedule (cron), webhook, or vercel_event / github_event / cursor_event / linear_event / slack_event / figma_event so checklists re-run on deploys, pull requests, or design updates

  • update_workflow

    Update a workflow's name, description, or trigger. Only the fields you pass change. Syncs the Trigger.dev schedule when the cron or trigger type changes. The trigger fields edit the workflow's one trigger; a workflow with several triggers has them edited in the dashboard instead.

  • toggle_workflow

    Activate or pause a workflow. Scheduled workflows have their Trigger.dev schedule activated/deactivated to match. Activating a workflow that runs on a schedule, webhook or event needs the mcp:run scope, since it then starts runs on its own; pausing never does. Pausing keeps the s

  • delete_workflow

    Delete a workflow and its steps and runs, and remove its schedule. This discards run history; prefer toggle_workflow to pause unless the user asks for deletion.

  • add_workflow_step

    Add a step to a workflow and connect it into the run. Only stores it: nothing executes until the workflow runs. Appends by default; `sort_order` splices it in at a position. In a run, run_checklist drives a real browser; notification emails or messages members on Slack; github_co

  • update_workflow_step

    Change a step's type or config in place, leaving its connections alone (move it with reorder_workflow_steps). Only stores the change. Config shapes are as in add_workflow_step.

  • remove_workflow_step

    Remove a step and close the gap: whatever led into it is repointed at whatever it led to, so the rest of the automation still runs.

  • reorder_workflow_steps

    Set the order a workflow runs its steps in, as one linear sequence. Pass every step id: a list that leaves a step out is refused, since that step would be disconnected from the run (remove it with remove_workflow_step instead). This rewires the whole automation, so a branch built

  • connect_workflow_steps

    Wire a step's output handle to another step, to build or repair a branch (adding and removing steps keeps the plain chain on their own). A condition's 'false' handle starts unconnected, so a failing condition ends the run. Connecting a connected handle replaces its edge; target_s

  • comment_on_pr

    Post a comment on a GitHub pull request via the workspace GitHub connection. Use it to report checklist or interview results where engineers already look: a short verdict, then per-check outcomes with evidence highlights. Needs the Stunt Double GitHub App installed on the reposit

  • list_pull_requests

    List pull requests for a GitHub repository via the workspace GitHub connection, most recently created first (up to 30). Use it to find the PR number to pass to get_pull_request or comment_on_pr.

  • get_pull_request

    Get details for a GitHub pull request (title, description, author, branches, change stats) via the workspace GitHub connection. Read it before writing a checklist for the change, then report back with comment_on_pr.

  • list_interviews

    List the user interviews in a workspace, newest first, optionally filtered to one project. Returns summary rows; call get_interview for the discussion guide and participants, or get_interview_report for the findings.

  • get_interview

    Get an interview with its discussion guide (sections and their items, in order) and participants with their run status. Also useful for polling progress after launch_interview; call get_interview_report for the synthesised findings.

  • create_interview

    Create a user interview: AI persona participants complete tasks and answer questions against target_url, and results are synthesised into a report. target_url can be any reachable URL, including prototypes (Figma Make publish links, Claude design artifacts, v0) and preview deploy

  • update_interview

    Update an interview’s name, target_url, research brief, status or usability questionnaire. Only the fields you pass change; pass at least one. To start a round use launch_interview rather than setting status to running.

  • add_interview_section

    Add a section to an interview’s discussion guide. Sections group related items (e.g. "First impressions", "Checkout"); add questions and tasks to it next with add_interview_item, using the returned id as section_id.

  • add_interview_item

    Add a question or task to an interview section (create the section first with add_interview_section). Tasks are concrete jobs to attempt in the product ("Find the annual plan price and compare it with monthly"); questions probe comprehension and sentiment. Set expected_evidence o

  • add_interview_participant

    Attach a participant to an interview. Provide either actor_id (existing actor) or persona_spec (ad-hoc persona: name, bio, traits), not both. Vary personas and devices across participants (expertise, motivation, scepticism, mobile vs desktop) for richer findings, and use behaviou

基本チェックi

誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月6日にチェック

  • ✓ 合格

    作者とリポジトリが一致

    レジストリ名はドメイン stuntdouble.io で確認済みです(レジストリがドメインの所有を確認しています)

  • … 未チェック

    今もメンテナンスされている

    このリポジトリはまだGitHubから読み取っていません

  • … 未チェック

    ライセンスがある

    このリポジトリはまだGitHubから読み取っていません

  • ✓ 合格

    エンドポイントが応答する

    394ミリ秒で応答(HTTP 200)

  • – 対象外

    OAuthでサインイン

    サインイン不要

  • ✓ 合格

    ツールの説明に隠れた指示がない

    60件のツールの説明を読み、AIへの隠れた指示は見つかりませんでした

開発者ツールのほかのサーバーとの比較i

  • このカテゴリのほかの1388件のうち0%よりスターが多い
  • このカテゴリのほかの1388件のうち96%より最近レジストリに公開
  • 基本チェックの結果が、このカテゴリのほかの1388件のうち100%と同じかそれ以上

レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。

よくある質問

Stunt Doubleは安全ですか?

当てはまる基本チェック3項目のうち3項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。

どんなキーやコードが必要ですか?

レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。

パソコンで動きますか、それともクラウドですか?

作者のクラウドで動きます。インストール不要でインターネット経由でつながりますが、送った内容は作者のサーバーを通ります。

今もメンテナンスされていますか?

GitHubリポジトリの最終更新は–、最新バージョン(1.17.0)がレジストリに届いたのは一昨日です。

どのアプリで使えますか?

Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。URLでつながるので、リモートMCPサーバーに対応したアプリ(開発者モードのChatGPTなど)でも使えます。

代わりに使えるものは?

同じカテゴリには:GitHub, Desktop Commander, Cloudflare MCP

代わりの候補

同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。

カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i

GitHub

作者:github

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

パソコンでもクラウドでも★ 34,245MIT3 日前更新
インストール

Desktop Commander

作者:wonderwhy-er

MCP server for terminal commands, file operations, and process management

パソコンで動く★ 10,225MIT15 日前更新
インストール

作者のREADME

READMEを開く

作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。

Stunt Double MCP Server

Deploy AI user personas to validate user journeys at scale. Find UX friction before real users do.

Stunt Double deploys AI agents with realistic user personas to validate user journeys at scale. Create actors, run automated workflows and checklists against any web app, and surface friction points before real users encounter them. Integrates with Claude, Linear, GitHub, and Slack.

Contents

  • This repository
  • Quick Start: Claude Code, Claude Code plugin, Skills, Claude, ChatGPT and Codex, Codex CLI, Gemini CLI, VS Code, OpenCode, Windsurf, Other clients, Cursor
  • Stunt Double Studio: Hooks, Local or cloud
  • Authentication: What a connection can reach
  • Available Tools: Account, Workspaces, Search, Projects, Guidelines, Actors, Knowledge, Conversations, Checklists, Workflows, Feedback, GitHub, Interviews, Prompts, Resources, Stunt Double Index
  • Example prompts: Demo targets
  • Privacy Policy
  • Support
  • Transport
  • MCP Registry
  • Links
  • Verifying changes
  • License

This repository

This repo holds plugin and MCP configuration (.claude-plugin/plugin.json and .mcp.json for Claude, .cursor-plugin/plugin.json, marketplace.json and root mcp.json for Cursor, server.json for the MCP registry), plus skills, agents, and Cursor rules. There is no `package.json` and no server code here: the MCP endpoint is hosted at https://app.stuntdouble.io/api/mcp from the main Stunt Double codebase, and the Claude plugin's local server is the published stuntdouble npm package from StuntKit. See CONTRIBUTING.md for how to validate edits and avoid confusing this folder with a Node package.

Quick Start

Claude Code
claude mcp add --transport http stuntdouble https://app.stuntdouble.io/api/mcp
Claude Code plugin

The repository is also a Claude plugin: it bundles the hosted MCP server and the Stunt Double Studio server (.mcp.json) with the skills in skills/, the agents in agents/ and the Studio hooks in hooks/.

claude plugin marketplace add stunt-double/stuntdouble-mcp

claude plugin install stuntdouble@stuntdouble

Type /stuntdouble: to list the plugin's skills. The Studio ones are /stuntdouble:setup, /stuntdouble:run, /stuntdouble:open, /stuntdouble:cloud and /stuntdouble:doctor.

Skills (any agent)

The skills in skills/ install into Claude Code, Cursor, Codex, OpenCode and other agents that read SKILL.md files, using the skills CLI. They drive the MCP server above, so connect that too.

npx skills add stunt-double/stuntdouble-mcp                          # pick from the list

npx skills add stunt-double/stuntdouble-mcp --skill verify-change # just one

SkillWhat it does
check-agent-readinessCheck how well AI agents (ChatGPT, Claude, Gemini, Perplexity and others) can find, understand and act on a website using the Stunt Double Index, explain the score from real agent sessions, compare against peers, and re-score after fixes
check-brandAudit a product or site against brand and tone-of-voice guidelines
check-complianceCheck a product against legal and compliance requirements on Stunt Double (cookie consent, privacy and terms access, required disclosures, claim substantiation, unsubscribe flows) and collect evidence for counsel to review
check-continuityCheck continuity across surfaces on Stunt Double
check-design-systemAudit a live product against its design system on Stunt Double
cloud/stuntdouble:cloud : push a Studio checklist to a workspace, run it there and pull it back. Needs the Claude Code plugin
create-actor-panelCreate and configure a Stunt Double actor (AI persona) with knowledge entries for realistic user simulation
design-reviewRun a design review session by gathering feedback from multiple Stunt Double actors on a proposed design or flow
doctor/stuntdouble:doctor: check Node, Chrome, the viewer port and how local runs are billed. Needs the Claude Code plugin
maintain-automationsChange an existing Stunt Double automation or checklist without losing run history: retime triggers, edit and rewire workflow steps, build condition branches, update checks in place, and pause or retire what is no longer needed
open/stuntdouble:open: open the Studio viewer over every run. Needs the Claude Code plugin
run/stuntdouble:run [resume]: run a Studio checklist in a local Chrome. Needs the Claude Code plugin
run-qa-suiteRun the full Stunt Double QA suite
run-user-interviewPlan, configure, and launch a structured user interview with AI participants on Stunt Double, then read back the synthesised report
run-ux-validationValidate a user journey by running Stunt Double workflows or checklists and reporting the results
setup/stuntdouble:setup for Stunt Double Studio: ready the project for local runs (dev server, actor and checklists, CLAUDE.md notes, permission and hooks). Needs the Claude Code plugin
setup-guardrailsStand up continuous guardrails on Stunt Double
triage-feedbackReview, categorize, and manage Stunt Double feedback submissions across projects
verify-changeVerify a shipped or previewed code change by running a Stunt Double actor through the affected user flows, and optionally report results on the pull request
Claude (web, Desktop, mobile)

Go to Settings → Connectors → Add custom connector and paste:

https://app.stuntdouble.io/api/mcp
ChatGPT and Codex

Connect the hosted server in ChatGPT developer mode (Settings → Apps → Advanced) as a custom connector with:

https://app.stuntdouble.io/api/mcp

The checklist run and Index report tools render as cards in ChatGPT (and in other MCP Apps hosts, Claude among them).

Codex CLI
codex mcp add stuntdouble --url https://app.stuntdouble.io/api/mcp

codex mcp login stuntdouble

Or add it to ~/.codex/config.toml by hand and then run codex mcp login stuntdouble:

[mcp_servers.stuntdouble]

url = "https://app.stuntdouble.io/api/mcp"

Gemini CLI
gemini mcp add --transport http stuntdouble https://app.stuntdouble.io/api/mcp

Or add it to ~/.gemini/settings.json (or .gemini/settings.json in a project):

{

"mcpServers": { "stuntdouble": { "httpUrl": "https://app.stuntdouble.io/api/mcp" } } }

Run /mcp auth stuntdouble inside Gemini CLI to sign in.

VS Code (GitHub Copilot)
code --add-mcp '{"name":"stuntdouble","type":"http","url":"https://app.stuntdouble.io/api/mcp"}'

Or add it to .vscode/mcp.json in a workspace (or run MCP: Open User Configuration for every workspace):

{

"servers": { "stuntdouble": { "type": "http", "url": "https://app.stuntdouble.io/api/mcp" } } }

The tools appear in Copilot Chat's agent mode.

OpenCode

Add it to opencode.json in a project (or ~/.config/opencode/opencode.json), then run opencode mcp auth stuntdouble:

{

冒頭だけを表示しています。続きはリポジトリで読めます

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