About surveyloop
surveyloop is a local bridge to Inquira's hosted survey service for creating, publishing, and analyzing AI-generated surveys. It covers the survey lifecycle through response retrieval and reports, while link distribution remains the caller's responsibility.
Key features
- 01Generate surveys from research goals
- 02Publish surveys and retrieve share links
- 03List surveys by status
- 04Retrieve submitted responses
- 05Generate AI analysis reports
Use cases
- 01Create a survey for customer research
- 02Publish a survey and obtain its link
- 03Review responses to a survey
- 04Produce survey insights and recommendations
MCP support
It exposes the captured Inquira tools to MCP clients and forwards tool calls to the hosted MCP server. It does not provide a tool for sending survey links.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
6Saved tool list · updated 1w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| goal | string | Yes | Describe what you want to research. E.g. 'Customer satisfaction survey for our SaaS product after onboarding' |
| lang | enum | No | Language for the survey content. Defaults to 'en'.en | zh | ja | es | pt |
| publish | boolean | No | Whether to immediately publish the survey after creation. Defaults to false. |
Details
From the project READMEsurveyloop
surveyloop is a small local bridge to the hosted Inquira MCP server, which runs AI surveys end to end. Describe a research goal and it generates a professional survey for it; from there you can publish the survey, share its link, read the responses that come back, and ask for an AI analysis report with an executive summary, key metrics, per-question insights and action recommendations.
The bridge keeps no survey data of its own. It serves the upstream server's tool list locally, exactly as captured from the live endpoint, and forwards each tool call upstream, returning the result untouched. The captured surface stops at returning a survey's own share link: sending that link to anyone is the caller's own act, and there is no outreach or sending tool in it.
Tools
create_survey— generate a survey from a research goal. Required:goal. Optional:lang(one of"en","zh","ja","es","pt"; defaults to"en") andpublish(publish immediately after creation; defaults to false). Returns the survey ID and shareable link.get_surveys— list all surveys belonging to the authenticated user. Optional:status(one of"all","published","draft"; defaults to"all").get_responses— get all responses submitted to a specific survey. Required:survey_id.get_ai_report— generate an AI analysis report for a survey's responses. Required:survey_id.publish_survey— publish a survey to make it accessible via its share link. Required:survey_id.get_survey_link— get the shareable link for a published survey. Required:survey_id.
Configuration
INQUIRA_MCP_URL(optional) — override the upstream endpoint. Defaults tohttps://getinquira.com/api/mcp. (The override hook is this rebuild's own labelled reconstruction.)INQUIRA_API_KEY(optional) — when set, every upstream request carries anAuthorization: Bearer <key>header, for the caller's own Inquira key. When it is not set, no key header is sent. (The header name is pinned by the original's registry record; the Bearer scheme and this env forwarding are labelled reconstructions — the original surface was captured keyless.)
Forwarding mechanics
On the first tool call the client opens a streamable
HTTP session with the upstream: a JSON-RPC
initialize request (protocolVersion 2025-03-26,
clientInfo name surveyloop), then a
notifications/initialized notification, then the
tools/call request carrying the caller's arguments
unchanged. When the upstream answers initialize
with an Mcp-Session-Id header, that value rides on
every later request of the session, which is reused
for the life of the process. Replies may arrive as
plain JSON or as server-sent events; both are read.
Successful upstream results pass through verbatim,
including any isError flag the upstream sets.
Failures — a JSON-RPC error, a non-2xx status, an
unreadable response, or a request that cannot be
completed — come back as an isError result whose
text starts with surveyloop error: (this rendering
is this rebuild's own labelled reconstruction).
CLI
Each tool is also a subcommand taking one JSON argument string:
npx @reneturcios/surveyloop create_survey '{"goal":"Customer satisfaction survey for our SaaS product after onboarding","lang":"en"}'
npx @reneturcios/surveyloop get_responses '{"survey_id":"sv_123"}'
npx @reneturcios/surveyloop --version
Exit codes: 0 on success, 1 on an isError
result, 2 on a usage error.
MCP server
npx -y @reneturcios/surveyloop mcp
MCP client config:
{
"mcpServers": {
"surveyloop": {
"command": "npx",
"args": ["-y", "@reneturcios/surveyloop", "mcp"]
}
}
}
Docker
docker run -i ghcr.io/cloudcorprecords/surveyloop
docker run --rm ghcr.io/cloudcorprecords/surveyloop --version
The container's default command is mcp, so the first
form is a stdio MCP server; any other arguments reach
the CLI normally.
Development
npm install
npm run build
npm test
npm run dev
The test suite runs entirely against a stubbed JSON-RPC upstream — no live network calls.
License
MIT — see LICENSE.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.