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
npx skills add stunt-double/stuntdouble-mcp --skill verify-change
| 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).
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:
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"stuntdouble": {
"type": "remote",
"url": "https://app.stuntdouble.io/api/mcp"
}
}
}
Windsurf
Add it to ~/.codeium/windsurf/mcp_config.json (or Windsurf Settings → Cascade → MCP Servers → View raw config):
{
"mcpServers": {
"stuntdouble": {
"serverUrl": "https://app.stuntdouble.io/api/mcp"
}
}
}
Other clients
Any client that speaks Streamable HTTP and OAuth can connect to https://app.stuntdouble.io/api/mcp directly. For a client that only runs local (stdio) servers, bridge it with mcp-remote, which handles the OAuth sign-in:
{
"mcpServers": {
"stuntdouble": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://app.stuntdouble.io/api/mcp"]
}
}
}
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.
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 |
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:
- 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."
- 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."
- 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?"
- 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
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
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