Usercall MCP
Usercall MCP - AI agents that run real user interviews
AI can build products. But it still doesn't talk to users.
Usercall MCP lets AI agents run user interviews via voice calls and return structured insights with themes and verbatim quotes.
Works with Claude Desktop, Cursor, and any MCP-compatible client.
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.
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
↓
Usercall Agent API
↓
Real user interviews
↓
Themes and verbatim quotes returned to the agent
Try it in 60 seconds
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"
}
}
}
}
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
Show participants this prototype during the interview:
https://www.figma.com/proto/abcd1234/onboarding-flow
The agent will:
- create a study
- return an interview link
- collect responses
- return themes and verbatim quotes
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
language: "en"
study_media:
type: "prototype"
url: "https://www.figma.com/proto/abcd1234/onboarding-flow"
description: "New onboarding flow concept"
Tools
create_study
Creates an interview study and returns an interview_link to share with participants.
| Field | Type | Required |
|---|---|---|
key_research_goal | string | yes |
business_context | string | yes |
additional_context_prompt | string | no |
target_interviews | number | no |
language | auto | en | ko | no |
duration_minutes | number | no |
metadata | object | no |
study_media | object | no |
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
Updates an existing study. Use this to increase interview slots, add/update media, or disable the link.
| Field | Type | Required |
|---|---|---|
study_id | uuid string | yes |
target_interviews | number | no |
is_link_disabled | boolean | no |
study_media | object | no |
The study_media object follows the same schema as in create_study.
get_study_status
Returns the current lifecycle status of a 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
Returns analysis output once the study is complete.
| Field | Type | Required |
|---|---|---|
study_id | uuid string | yes |
format | summary | full | no |
Summary/full responses include study progress fields and analysis output.
delete_study
Permanently deletes a study and all associated data (recordings, transcripts). Releases unused reserved credits.
| Field | Type | Required |
|---|---|---|
study_id | uuid string | yes |
Example workflow
1. create_study
key_research_goal: "Why do users drop off during onboarding?"
business_context: "B2B SaaS, 3-step signup flow"
→ returns { study_id, interview_link }
2. Share interview_link with participants
(email, Slack, in-product prompt, etc.)
3. get_study_status
→ "analyzing"
4. get_study_results
→ themes + verbatim quotes returned to the agent
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. Share interview_link — participants see the mockup during interview
For Figma prototypes, use type: "prototype" with a Figma proto URL.
Requirements
- Node.js 18+
- A valid Usercall API key
Self-hosting / development
pnpm install
pnpm build
USERCALL_API_KEY="your_key_here" pnpm start
Smoke test:
USERCALL_API_KEY="your_key_here" pnpm smoke
Troubleshooting
| Error | Fix |
|---|---|
Missing USERCALL_API_KEY | Set the env var before starting |
401 Unauthorized | Invalid or revoked API key |
402 Insufficient credits | Add credits at app.usercall.co |
500 on create | Verify your key has access to Agent API v1 |
License
MIT
Server Config
{
"mcpServers": {
"usercall": {
"command": "npx",
"args": [
"-y",
"@usercall/mcp"
],
"env": {
"USERCALL_API_KEY": "your_key_here"
}
}
}
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