Stunt Double

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.

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 runnable server here: the MCP endpoint is hosted at https://app.stuntdouble.io/api/mcp from the main Stunt Double codebase. 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 (.mcp.json) with the skills in skills/ and the agents in agents/.

claude plugin marketplace add stunt-double/stuntdouble-mcp
claude plugin install stuntdouble@stuntdouble

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

Skill	What it does
check-agent-readiness	Check 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-brand	Audit a product or site against brand and tone-of-voice guidelines
check-compliance	Check 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-continuity	Check continuity across surfaces on Stunt Double
check-design-system	Audit a live product against its design system on Stunt Double
create-actor-panel	Create and configure a Stunt Double actor (AI persona) with knowledge entries for realistic user simulation
design-review	Run a design review session by gathering feedback from multiple Stunt Double actors on a proposed design or flow
maintain-automations	Change 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
run-qa-suite	Run the full Stunt Double QA suite
run-user-interview	Plan, configure, and launch a structured user interview with AI participants on Stunt Double, then read back the synthesised report
run-ux-validation	Validate a user journey by running Stunt Double workflows or checklists and reporting the results
setup-guardrails	Stand up continuous guardrails on Stunt Double
triage-feedback	Review, categorize, and manage Stunt Double feedback submissions across projects
verify-change	Verify 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

The repository also carries an OpenAI plugin manifest (.openai-plugin/plugin.json, in the Agent Plugins format) with the directory listing, review test cases and release notes. node scripts/build-openai-plugin.mjs checks it against OpenAI's limits and writes dist/stuntdouble-openai-plugin.zip (in the Codex layout the portal accepts: the manifest as .codex-plugin/plugin.json, a .mcp.json for the hosted server, the skills and the logos), which is what goes into the plugin submission portal.

Until it is published in the directory, connect it 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).

Cursor

This repository is a Cursor plugin: .cursor-plugin/plugin.json and .cursor-plugin/marketplace.json, root mcp.json (the hosted MCP server), plus the skills in skills/, rules in rules/, and agents in agents/. The plugin logo is assets/logo.png. Auth is OAuth 2.1 with PKCE; no API keys.

Install as a plugin (recommended): once published, install Stunt Double from the Cursor marketplace. For a team marketplace or local clone, add this repo as a marketplace and install the stuntdouble plugin; Cursor discovers the MCP server, skills, rules and agents from the default folders.

MCP only (no skills, rules or agents): add the block below to a Cursor MCP config:

• Project-local: .cursor/mcp.json at the root of your project.
• Global (all projects): ~/.cursor/mcp.json on macOS/Linux (see Cursor MCP docs for your OS).

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

Use only url for remote servers (Streamable HTTP is negotiated automatically). Extra keys such as "type": "streamable-http" are not part of Cursor's documented mcp.json shape and can break plugin validation.

The server.json file is the separate MCP registry manifest for mcp-publisher and directory listings; Cursor's installer does not use it.

Windsurf

Add the same mcpServers block as under Cursor (MCP only) to Windsurf's MCP config.

Authentication

Authentication is handled automatically via OAuth 2.1 with PKCE. The first time your AI client connects, a browser window will open for you to sign in and authorise access to your Stunt Double account. No API keys or tokens required.

For Cursor, the OAuth redirect URI is fixed to cursor://anysphere.cursor-mcp/oauth/callback (docs).

What a connection can reach

The server acts as you, never more. Every tool resolves the workspace it is being asked about and checks your membership of it before doing anything, so a connection reaches exactly the workspaces list_workspaces returns for you, and an archived workspace reaches nothing. A workspace you are not a member of answers the same way one that does not exist does: "not found".

That holds for ids too, not just the workspace_id you pass. A tool that takes another object's id (a checklist for an automation step, an actor for an interview participant) checks that object belongs to the same workspace before storing or running it, and refuses with "not found in this workspace" otherwise. Refusals never say which workspace an id does belong to.

Scopes narrow this further, never widen it. The consent screen names what the connection asked for, and a token granted mcp:read is not shown the write or run tools at all: they are absent from tools/list rather than present and failing.

Scope	What it allows
mcp:read	Read your workspaces and their contents
mcp:write	Create and edit content in your workspaces
mcp:run	Start checklist runs, automation runs and interviews, which consume the workspace run allowance, and re-run Stunt Double Index scores for domains you own

Available Tools

Account

Tool	Description
get_me	The account this connection acts as: id, email, name, timezone, notification channel

Notification channel and timezone are account settings rather than workspace ones, so they are the same answer in every workspace. Pass the timezone when creating a scheduled workflow, or "every weekday at 9" becomes nine in UTC.

Workspaces

Tool	Description
list_workspaces	List your workspaces
get_workspace	Get workspace details by ID or slug, including its admin-set controls (settings)
list_workspace_members	List members of a workspace

get_workspace reports the workspace security controls under settings: public sharing, the feedback widget, self-hosted workers, and the network policy. They are ceilings set by an admin, so a feature switched off there cannot be switched back on for a single project.

Search

Tool	Description
search	Search a workspace across projects, actors, checklists, interviews, automations, issues, goals, feedback, actor knowledge, insights, design reviews, project resources and conversations. Ranked, with optional filters

search takes a workspace_id plus an optional query, types filter, project_id filter and limit (max 50). Terms are matched as prefixes, so a partial word is enough. Omit query to browse the most recently updated items. Results carry the id you need for the matching getter, so it is usually cheaper than listing an entity type and filtering the list yourself. Reach for it before creating anything, to find the actor or checklist that already covers the job.

Projects

Tool	Description
list_projects	List projects in a workspace
get_project	Get a project (the product tracked by checklists, workflows, feedback)
create_project	Create a project (a product to track with checklists, workflows, feedback)
list_project_mcp_servers	The MCP servers this project's runs can reach

A project is archived, never deleted, and an archived project reads as missing from every tool here. Registering an MCP server and attaching it to a project are workspace-admin actions in the dashboard; list_project_mcp_servers is how you check what tools a run will actually have before writing a checklist that depends on one.

Guidelines

Standing rules the team holds the product to: design system, tone of voice, brand, content, accessibility, compliance, security, performance, or shared knowledge. A guideline is owned by the workspace and attached to the projects it applies to, so one rule can hold for every project without being retyped. Whatever is in force is rendered into every checklist run, design review, interview and triage for that project.

Tool	Description
list_workspace_guidelines	The workspace library, with how many projects hold each rule
add_workspace_guideline	Add a rule to the library, optionally attaching it to projects
update_workspace_guideline	Edit a rule, switch it off, or apply it to every design review in the workspace
remove_workspace_guideline	Remove a rule from the library, detaching it from every project
list_project_guidelines	The rules this project is held to
add_project_guideline	Record a rule and hold this project to it
set_project_guideline	Attach a library rule to a project, detach it, or switch it off there

Two switches decide whether a rule is in force for a project: the library's enabled and the attachment's. list_project_guidelines folds them into one enabled so you never have to reason about both. A rule with apply_to_design_reviews set also holds for design reviews raised from Slack or Linear, which carry no project to attach it through.

Codify a standard as a guideline rather than repeating it in each checklist, and search the library before writing a new rule: attaching the one that already exists keeps the team's standard in a single place to edit.

Actors

Tool	Description
list_actors	List active actors in a workspace
get_actor	Get actor details including system prompt and capabilities
create_actor	Create a new actor in a workspace
update_actor	Update actor name, description, system prompt, capabilities, or status. Set status to "archived" to soft-delete

Knowledge

Tool	Description
list_actor_knowledge	List knowledge entries for an actor
add_actor_knowledge	Add a knowledge entry to an actor
remove_actor_knowledge	Remove a knowledge entry

Conversations

Tool	Description
list_conversations	List conversations, optionally filtered by actor
get_conversation	Get a conversation with its messages

Checklists

Tool	Description
list_checklists	List checklists in a workspace
get_checklist	Get checklist details, checks, and recent runs
get_checklist_run	Get a checklist run with per-check results
run_checklist	Trigger a checklist run (async). Returns run ID
create_checklist	Create a browser-based QA checklist (host via project or URL, actor, instructions, checks)
update_checklist	Update a checklist (pass checks to replace the full set)
delete_checklist	Delete a checklist and its checks and runs

Workflows

A workflow is a graph, not a list: its steps run by following the connections between them. The step tools maintain those connections, so adding, removing and reordering steps is enough to build one. connect_workflow_steps is only needed to branch.

Tool	Description
list_workflows	List workflows in a workspace
get_workflow	Get a workflow with its steps, edges, the order a run takes, and recent runs
run_workflow	Trigger a workflow run (async). Returns run ID
get_workflow_run	Get a workflow run with step-level details
create_workflow	Create a workflow (multi-step automation)
update_workflow	Update a workflow's name, description, or trigger
toggle_workflow	Activate or pause a workflow
delete_workflow	Delete a workflow and its steps and runs
add_workflow_step	Add a step and connect it into the run
update_workflow_step	Change a step's type or config in place
remove_workflow_step	Remove a step and close the gap it leaves
reorder_workflow_steps	Set the order the steps run in
connect_workflow_steps	Wire one step to another, for a condition's True and False paths

Feedback

Tool	Description
list_feedback	List feedback for a project, newest first
get_feedback	Get a feedback submission with its replies
update_feedback_status	Update feedback status

GitHub

Tool	Description
list_pull_requests	List pull requests for a GitHub repository
get_pull_request	Get details for a GitHub pull request (title, author, branches, stats)
comment_on_pr	Post a comment on a GitHub pull request

Interviews

Structured user interviews: actors or generated personas run through a discussion guide (sections + questions/tasks) against a target URL, then Stunt Double synthesises themes and recommendations.

Tool	Description
list_interviews	List interviews in a workspace, optionally filtered by project
get_interview	Get an interview with its discussion guide (sections + items) and participants
create_interview	Create a new interview in a project (name, target URL, research brief)
update_interview	Update an interview's name, target URL, research brief, or status
add_interview_section	Add a section to the discussion guide
add_interview_item	Add a question or task to a section
add_interview_participant	Attach a participant, either an existing actor or an ad-hoc persona_spec
get_interview_participant	Get a participant including their full transcript from the run
get_interview_report	Get the current synthesised report (summary, themes, recommendations, per-question rollup)
launch_interview	Launch the interview round (async). Returns the trigger run ID
regenerate_interview_report	Re-run synthesis on existing transcripts (async). Returns the trigger run ID

Prompts

Most MCP clients (Claude, Claude Code, Cursor) surface these as slash commands. Each is a self-contained recipe: which tools to call, in what order, and how to report back.

Prompt	Description
validate_design	Validate a live design, prototype, or preview URL (Figma Make, Claude artifact, v0, staging) with AI personas
verify_change	Verify a shipped or previewed code change by running an actor through the affected flows, optionally commenting on the PR
run_user_research	Run a structured multi-persona interview study and synthesise themes and recommendations
triage_feedback	Triage user feedback on a project: cluster it, reproduce issues with an actor, and update statuses
setup_guardrails	Stand up checklists for critical flows plus a workflow that re-runs them on a schedule or on deploy/PR events
check_brand	Audit a product against brand and tone-of-voice guidelines, flagging deviations with evidence
check_design_system	Audit a live product against its design system (typography, colour, spacing, components) on rendered pages
check_compliance	Check a product against legal and compliance requirements and collect evidence for counsel to review
check_continuity	Check continuity across surfaces (pricing, terminology, promises) between marketing, product, docs, and emails
stuntdouble_guide	Orientation for Stunt Double: what it does, when to reach for it, and the full tool catalogue

Resources

Read-only context a client can attach without calling a tool. The guide and the connection are always listed; the workspace resources need mcp:read, the same as the tools that return that data.

URI	MIME type	Description
stuntdouble://guide	text/markdown	What Stunt Double does, when to reach for it, the full tool catalogue and how to poll a run
stuntdouble://connection	application/json	Who the connection acts as, the scopes it holds, the tools each unlocks and any it lacks
stuntdouble://workspaces	application/json	The workspaces the connection can reach, with your role (same data as list_workspaces)
stuntdouble://workspaces/{workspace_id}/projects	application/json	The live projects in one workspace, most recently opened first (same data as list_projects)

resources/list includes one projects entry per workspace, so a client can browse them without expanding the template.

Stunt Double Index

The Stunt Double Index is a public ranking of how AI agents experience websites: each tracked domain is scored out of 100 from HTTP probes plus live agent sessions, one per AI provider and benchmark task. Index data is public rather than workspace data, so the read tools reach any tracked site.

Tool	Description
get_index_report	A site's score, band, rank, category and provider scores, frictions, failing probe checks and when it was last scored
list_index_sessions	The agent sessions behind a score (newest run by default), with status, score, evidence, a summary and frictions. Filter by provider or category
search_index_domains	Find a site by domain or name, or browse the leaderboard, optionally by sector
request_index_rerun	Re-score a domain you own (mcp:run). Fresh probes now, about 24 agent sessions over a few minutes. Once every 10 minutes

get_index_report, list_index_sessions and request_index_rerun take a domain, or a project_id to use the Index domain linked to that project (which checks your membership like any project read). Only the domain's owner can re-run it: a platform admin, the person who claimed it, or, while it is unclaimed, someone signed in with a work email on that exact domain. After a re-run, poll list_index_sessions with the returned run_id until the sessions finish, then read get_index_report. (inviting/removing members) is available in the web dashboard.

Example prompts

Four prompts that exercise the core of the server once it is connected:

1. Verify a flow: "Create a checklist that signs up for a new account on https://demo-checkout-stunt-double.vercel.app, adds an item to the basket and reaches payment, then run it and tell me which checks failed."
2. Run a user interview: "Set up an interview with three personas (a first-time shopper, a returning customer and a screen reader user) about our pricing page, launch it, and summarise the report."
3. Check agent readiness: "How well can AI agents use stripe.com according to the Stunt Double Index, and which categories are dragging its score down?"
4. Triage feedback: "Summarise the open feedback on my main project, group it into themes, and mark anything already fixed as resolved."

Privacy Policy

The server is hosted by Stunt Double and acts as the signed-in user. It reads and writes only the workspaces that user belongs to, within the OAuth scopes they grant (mcp:read, mcp:write, mcp:run). It does not read your conversation with the AI client beyond the arguments passed to each tool call, and it does not access the client's memory, chat history or files.

Data created through the server (projects, actors, checklists, runs, interviews, feedback) is stored in your Stunt Double workspace and handled under the Stunt Double Privacy Policy, which covers collection, use, storage, sub-processors, retention and your rights. Revoke a connection at any time by disconnecting it in your AI client.

Support

• Email: support@stuntdouble.io
• Help centre and docs: stuntdouble.io/support
• MCP reference: stuntdouble.io/support/docs/api/mcp
• Security reports: see SECURITY.md

Transport

This server uses Streamable HTTP transport. The endpoint is:

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

MCP Registry

The server is listed in the official MCP Registry as io.stuntdouble/mcp-server, so registry-backed clients and directories can find it by name:

curl "https://registry.modelcontextprotocol.io/v0.1/servers?search=io.stuntdouble/mcp-server"

Each version merged to main is published there automatically (see CONTRIBUTING.md).

Links

• Website
• Documentation
• MCP server reference
• Privacy Policy
• Terms of Service
• llms.txt

Verifying changes

From the repo root:

node scripts/validate-json.mjs
npx --yes prettier@3.4.2 --check README.md CONTRIBUTING.md SECURITY.md CHANGELOG.md mcp.json .mcp.json server.json .cursor-plugin/plugin.json .cursor-plugin/marketplace.json .claude-plugin/plugin.json .claude-plugin/marketplace.json

More context in CONTRIBUTING.md. GitHub Actions runs the same checks on push and pull requests.

License

MIT