Usercall MCP - AI agents that run real user interviews

AI can build products. But it still doesn't talk to users.

Give your AI agents the ability to ask real users why.

Usercall MCP runs AI-moderated voice or text interviews with real users. Use it to learn why users churn, where onboarding drops off, or why an action failed, and get themes, insights, and verbatim quotes.

Why this exists

AI agents can now build and ship products extremely quickly.

But most agents still rely on synthetic feedback or assumptions about users.

Usercall MCP lets agents gather real qualitative feedback directly from users.

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Choose a connection

Recommended: hosted MCP (Claude, ChatGPT, Cursor, Grok Bot)

Add https://mcp.usercall.co as a remote MCP connector / custom connector.

• OAuth sign-in (no API key, no npx)
• Same tools as this package (studies + Research Triggers)
• Docs: app.usercall.co/docs/mcp
• Cursor Directory / Grok Bot: this repo ships .mcp.json so cursor.directory can install the hosted connector. Grok Bot cannot run the local npx package.

This package: local / API-key / machine-to-machine

Use @usercall/mcp over stdio when you want a Bearer API key (scripts, local clients, M2M).

1. Sign in at app.usercall.co → Home → Developer → Create API key
2. Run npx -y @usercall/mcp with USERCALL_API_KEY

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Example workflow

Agent: "Why are users confused about onboarding?"

→ create_study
→ share interview_link with users
→ get_study_results

The returned interview_link can be shared with participants through email, Slack, Discord, or in-product prompts.

Example result:

{
  "themes": [
    {
      "name": "Onboarding confusion",
      "summary": "Users struggled to understand the second step.",
      "quotes": [
        "I wasn't sure what the app was asking me to do.",
        "I didn't know I had to verify my email before continuing."
      ]
    },
    {
      "name": "Pricing confusion",
      "summary": "Free plan limits were not clearly communicated.",
      "quotes": ["I wasn't sure if the free plan included analytics."]
    }
  ]
}

How it works

AI Agent

↓

Usercall MCP (hosted OAuth or this stdio package)

↓

Usercall Agent API

↓

Real user interviews

↓

Themes and verbatim quotes returned to the agent

With Research Triggers, the agent can also target users in your product:

Analytics MCP (PostHog, Mixpanel, …) finds a behavior

↓

Usercall MCP creates a study and a paused Research Trigger

↓

You activate it in Usercall

↓

The Usercall SDK invites matching users to an interview right after the behavior

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Research Triggers

Analytics tells an agent what users do. Research Triggers let it ask them why.

User:  "Look at our PostHog data and find something worth investigating."

Agent (PostHog MCP):  users who test a study rarely launch one.

Agent (Usercall MCP):
  list_trigger_events()                  → study_tested, study_launched, …
  get_trigger_event_schema("study_tested")
                                         → properties: source, interview_type
                                           traits: plan ("free", "pro"), account_type
  create_study(...)  or  list_studies()
  create_research_trigger({
    study_id, event_name: "study_tested",
    traits: { plan: "free" }, sampling_percent: 25, max_invites_per_day: 10
  })                                     → status: "paused", summary, activation_url

Agent: "I've prepared a Research Trigger. When: study_tested · Audience: plan = free ·
        25% sampled · max 10 invites/day. It's paused. A human activates it here: <activation_url>"

• The Usercall SDK has to be installed. If list_trigger_events returns nothing, call get_trigger_sdk_setup (with your analytics provider and event names) to get the snippet. Coding agents can install it for you.
• Only events Usercall has actually received can be used. Filters are exact matches on event properties or user traits. get_trigger_event_schema shows which field is which.
• Unsupported conditions are rejected, not silently dropped. These include event counts, sequences, absence ("did not do X"), time windows, and not-equals. get_trigger_capabilities returns the full list.

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Local install (API key)

1. Get an API key

Sign in at app.usercall.co → Home → Developer → Create API key

2. Add to your MCP client

Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "usercall": {
      "command": "npx",
      "args": ["-y", "@usercall/mcp"],
      "env": {
        "USERCALL_API_KEY": "your_key_here"
      }
    }
  }
}

Cursor (.cursor/mcp.json):

{
  "mcpServers": {
    "usercall": {
      "command": "npx",
      "args": ["-y", "@usercall/mcp"],
      "env": {
        "USERCALL_API_KEY": "your_key_here"
      }
    }
  }
}

For Claude, ChatGPT, or Cursor remote connectors, prefer https://mcp.usercall.co instead of this JSON config.

Restart your MCP client.

3. Ask your agent

Run user interviews to understand why users drop off during onboarding.

Context:
- B2B SaaS product
- 3-step signup flow

Goal:
Identify confusion points and friction.

Target interviews: 5
Language: ko
Interview mode: voice

Show participants this prototype during the interview:
https://www.figma.com/proto/abcd1234/onboarding-flow

The agent will:

1. create a study
2. return an interview link
3. collect responses
4. return the summary (themes, insights, and risks)

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Structured tool example

Equivalent create_study tool call:

create_study
key_research_goal: "Understand why users drop off during onboarding"
business_context: "B2B SaaS signup flow"
target_interviews: 5
languages: ["en"]
interview_mode: "voice"

study_media:
  type: "prototype"
  url: "https://www.figma.com/proto/abcd1234/onboarding-flow"
  description: "New onboarding flow concept"

---

Tools

create_study

Create an AI-moderated interview study to learn why users churn, drop off in onboarding, fail an action, or where a product assumption is wrong. Returns study_id and interview_link for a voice, text, or voice-and-text interview. key_research_goal is required and cannot be changed later. business_context is optional. Defaults: target_interviews 1, duration_minutes 12, interview_mode voice. One active agent study per account. Does not run the interview or invite a participant. HTTP 402 includes checkout_url.

Field	Type	Required	Default
key_research_goal	string (5–2000)	yes
business_context	string (5–2000)	no
additional_context_prompt	string	no
target_interviews	number (1–200)	no	1
languages	string[]	no
duration_minutes	number (5–65)	no	12
interview_mode	voice | text | voice_and_text	no	voice
voice_gender	female | male	no
enable_link_context	boolean	no
custom_link_variables	{ key, label?, default_value? }[]	no
metadata	object	no
study_media	object	no

One locale turns the language picker off; two or more turn it on. Research goal cannot be changed after create.

study_media (optional). Visual stimulus shown during all interview questions:

Field	Type	Required
type	image | prototype	yes
url	string (URL)	yes
description	string (max 500 chars)	no

• image: Direct image URL (.png, .jpg, .gif, .webp)
• prototype: Figma prototype URL (converted to interactive embed)
• Media is only visible to web participants; phone callers won't see it

update_study

Update an interview study: slots, guide questions, intro, languages, voice, or an image or Figma prototype shown to participants. Returns the updated study. key_research_goal cannot be changed. is_link_disabled true stops new interviews and keeps recordings. One locale hides the language picker; two or more show it. Query parameters on interview_link are ignored until enable_link_context is true. study_media null clears media. API errors include http_status. Does not dry-run the guide or invite a participant.

Field	Type	Required
study_id	uuid string	yes
target_interviews	number (1–200)	no
is_link_disabled	boolean	no
ai_agent_intro_message	string	no
key_learning_goals	string	no
workflow_end_message	string	no
workflow_questions	{ text, ... }[]	no
interview_mode	voice | text | voice_and_text	no
languages	string[]	no
voice_gender	female | male	no
enable_link_context	boolean	no
custom_link_variables	{ key, label?, default_value? }[]	no
study_media	object or null	no

Pass study_media: null to clear media. The study_media object follows the same schema as in create_study.

get_study_status

Check whether user interviews are still running, being analyzed, or complete. Returns completed_interviews, target_interviews, interview_link, and next_step. running and analyzing include no findings, themes, or quotes. Does not change the study.

Field	Type
study_id	uuid string

Status values: running · analyzing · complete

Response includes interview progress fields, including completed_interviews and target_interviews.

get_study_results

Get interview findings after real users have talked: themes, insights, risks, and verbatim quotes. format omitted or summary returns themes, insights, and risks. format=full also returns transcripts. Empty themes mean analysis is not ready. Does not create interviews or edit the guide.

Field	Type	Required
study_id	uuid string	yes
format	summary | full	no

Summary/full responses include study progress fields and analysis output.

simulate_interview

Dry-run an interview guide before a real participant joins, including a question about churn, onboarding, or a failed action. Omit simulation_id to start; returns immediately with status running and a simulation_id. Pass simulation_id to read that run. Result status is pass, fail, or error. Max 5 simulations per account per UTC day. HTTP 429 means the daily cap is reached. Optional persona has name and prompt. A dry-run does not change completed_interviews and does not invite a participant.

Field	Type	Required
study_id	uuid string	yes
simulation_id	uuid string	no
persona	{ name, prompt }	no

Omit simulation_id to POST /api/v1/agent/studies/{studyId}/simulations. Pass simulation_id to GET that simulation. The tool does not poll.

review_study

Review an interview guide and return a written critique of the questions before real users see them. Reads the guide only: no transcripts, and suggested edits are not applied. Costs 1 credit. Request is study_id only; call_ids are not accepted. Works when the in-app review control is hidden. HTTP 402 includes checkout_url. Does not return themes, quotes, or other findings.

Field	Type	Required
study_id	uuid string	yes

Sends study_id only. It does not send call_ids.

delete_study

Permanently delete an interview study, its recordings, and unused reserved credits. Cannot be undone. Does not delete in-product research triggers.

Field	Type	Required
study_id	uuid string	yes

Research Trigger tools

Tool	Purpose
get_trigger_capabilities	Which in-product trigger conditions work. One event, exact property or trait, URL rule, page dwell. No counts, sequences, absence, time windows, or not-equals
get_trigger_sdk_setup	Snippet for product events (failed action, onboarding, churn). install_snippet, identify_snippet, allowlist_update_snippet. No secret keys
list_trigger_events	Product event names from the last 30 days. A trigger accepts only an observed name
get_trigger_event_schema	Fields on one product event, with types and sample values. Exact, case-sensitive, type-sensitive
list_studies	Existing interview studies: study_id, interview_link, interview_mode, trigger_eligible
create_research_trigger	Paused invite after a product moment (failed action, churn, onboarding). Returns activation_url
list_research_triggers	In-product triggers with status and activation_url
get_research_trigger	One trigger: who it invites, activation_url, invite and interview counts. No themes or quotes
update_research_trigger	Who gets invited. status: "active" is rejected (409). Editing an active trigger pauses it
delete_research_trigger	Permanently delete a trigger. Completed interviews stay on the study

create_research_trigger

Field	Type	Required	Default
study_id	uuid string	yes
event_name	string (from list_trigger_events)	yes
properties	object of exact-match values	no
traits	object of exact-match values	no
url	{ match: equals | contains | starts_with, value }	no
dwell_seconds	1–600 (page-visit triggers only)	no
source	page_visit | analytics_event | custom	no
sampling_percent	1–100	no	100
cooldown_days	0–365	no	30
max_invites_per_day	1–100	no	100
intercept_title	string (≤120), small label above the prompt	no	default
intercept_body	string (≤500), prompt text	no	default
delivery_method	intercept | webhook	no	intercept
webhook_url	public https URL (required for webhook)	no
webhook_secret	string (16–200), HMAC key, write-only	no
invite_link_params	{ static?, from_traits?, from_properties? }	no
name	string (≤100)	no	generated

For page-visit triggers, use source: "page_visit" and event_name: "$pageview", with url and optionally dwell_seconds.

Delivery.

• intercept (default) shows the Usercall widget in your product, and the user takes a voice or text interview in the page. The modes come from the study; list_studies returns each study's interview_mode.
• webhook POSTs each matched user to webhook_url, with their user ID, email if known, traits, event properties and a personal interview link. If webhook_secret is set, requests carry an x-usercall-signature HMAC header.
• Only public https URLs are accepted, and the activation page shows the destination before a person activates the trigger.

Safety

• Agents cannot activate triggers. Triggers are always created paused. Calling update_research_trigger with status: "active" returns HTTP 409 and the activation_url. A person has to open that link, review who will be invited, what they will see and the credit cost, and click Activate.
• Changes to an active trigger need re-approval. Changing an active trigger's configuration pauses it again.
• Secret keys are never returned. The ingestion secret key never comes back from any tool.

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Example workflow

1. create_study
   key_research_goal: "Why do users drop off during onboarding?"
   business_context: "B2B SaaS, 3-step signup flow"
   target_interviews: 5
   languages: ["ko"]
   interview_mode: "voice"

   → returns { study_id, interview_link }
   (`business_context` is optional; `key_research_goal` alone still creates a study)

2. simulate_interview
   study_id
   → running, simulation_id
   call again with simulation_id
   → pass, fail, or error

3. review_study
   study_id
   → guide check only; write changes with update_study

4. Share interview_link with participants
   (email, Slack, in-product prompt, etc.)

5. get_study_status
   → "analyzing"

6. get_study_results
   → summary: themes, insights, and risks
   use format=full only for a quote

With visual stimulus

1. create_study
   key_research_goal: "Get feedback on new dashboard design"
   business_context: "Redesigning analytics dashboard for power users"
   study_media:
     type: "image"
     url: "https://example.com/dashboard-mockup.png"
     description: "New dashboard design concept"

   → returns { study_id, interview_link }

2. After simulate_interview passes, a human shares interview_link. Participants see the mockup during the interview.

For Figma prototypes, use type: "prototype" with a Figma proto URL.

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Requirements

• Node.js 18+
• A valid Usercall API key (local / API-key path only)

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Self-hosting / development

pnpm install
pnpm build
USERCALL_API_KEY="your_key_here" pnpm start

Tests and smoke tests:

pnpm test                                   # unit + MCP contract tests
USERCALL_API_KEY="your_key_here" pnpm smoke # creates a real study
USERCALL_API_KEY="your_key_here" SMOKE_STUDY_ID="<uuid>" SMOKE_EVENT_NAME="<observed event>" pnpm smoke:triggers

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Official MCP Registry

Usercall is listed on the Official MCP Registry as co.usercall/mcp.

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Troubleshooting

Error	Fix
Missing USERCALL_API_KEY	Set the env var before starting this stdio package
401 Unauthorized	Invalid or revoked API key
402 Insufficient credits	Open the returned checkout_url, or add credits at app.usercall.co
500 on create	Verify your key has access to Agent API v1
event_not_observed	Usercall hasn't received the event. Add it to your SDK allowlist (get_trigger_sdk_setup(events=[...])), trigger it in your app, then retry
wrong_placement	The field is a trait, not a property (or the reverse). Use the suggested fix in the error
Trait filters never match	Call window.usercall.identify({ userId, traits }) when the user is known (see identify_snippet)
webhook_url_not_allowed	Use a public https URL, without credentials; localhost and private IPs are rejected
409 activation_required	Expected: agents can't activate. Share activation_url with the user
429 on simulate_interview	Cap is 5 simulations per account per UTC day. Stop for the day
Active trigger never fires	Check the event is still arriving (list_trigger_events), and check the values match exactly (case and type)

Remote Claude / ChatGPT / Cursor connectors should use https://mcp.usercall.co (OAuth). This package is the API-key stdio path.

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License

MIT