SurveyMonkey MCP

Live

OAUTH 2.0

ANALYTICS

Analytics

Connect to SurveyMonkey MCP. Create surveys, collect responses, and analyze results from your AI workflows using SurveyMonkey's research platform.

  • Acts as the user: Every tool call runs as the authorizing user. Access and audit trail stay intact.
  • Credentials stay vaulted: AES-256 encrypted, resolved at request time, never stored in LLM context.
  • Scoped before every call: Per-user permissions enforced automatically. 90-day audit trail included.
SurveyMonkey MCP
agent · Acme Q3
Run
Add Page in SurveyMonkey MCP
S
surveymonkeymcp_add_page
85ms
SurveyMonkey MCP agent
Add a new page to a survey at the specified position. only needed for multi-page surveys — new surveys already have a de.
Sources: SurveyMonkey MCP
surveymonkeymcpmcp
1 tool call
18:29
Message Claude...

SurveyMonkey MCP tools for AI agents

CALL ANY TOOL
12 tools covering create, get, list.
surveymonkeymcp_add_page
Add a new page to a survey at the specified position. only n
Add a new page to a survey at the specified position. only needed for multi-page surveys — new surveys already have a default page from create_survey. blocked on surveys with existing responses.
Parameters
Name
Type
Required
Description
page
object
Required
Page object describing the new page. May include fields such as 'title', 'description', and 'questions'. Example: {"title": "Section 2", "description": "Follow-up questions"}.
position
integer
Required
1-based position at which to insert the new page within the survey. Use 1 to insert before all existing pages. Example: 2 to insert as the second page.
survey_id
string
Required
ID of the survey to add a page to. Returned by create_survey. Accepts string or integer. Example: '123456789'.
surveymonkeymcp_add_question
Add a question to a survey page. requires survey_id, page_id
surveymonkeymcp_create_survey
Create a new empty survey with the given title. returns the
surveymonkeymcp_create_weblink_collector
Create a weblink collector for a survey, generating a public
surveymonkeymcp_delete_question
Permanently delete a question from a survey page. requires s
surveymonkeymcp_edit_question
Edit a single question's text, required status, answer choic
surveymonkeymcp_generate_survey_plan
Generate an ai-powered survey plan from a natural language d
surveymonkeymcp_get_page
Get details about a specific page in a survey. requires both
surveymonkeymcp_get_pages
Get all pages in a survey. use page ids returned here with g
surveymonkeymcp_get_question
Get details about a specific question. requires survey_id, p
surveymonkeymcp_get_question_types
Get available surveymonkey question types and their schemas.
surveymonkeymcp_get_questions
Get all questions for a specific page in a survey. both surv
Build your Agent
Same auth pattern across every framework.
Python · LlamaIndex
from langchain_mcp_adapters.client import MultiServerMCPClient
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="surveymonkeymcp")

mcp = MultiServerMCPClient({
"surveymonkeymcp": {
"url": "https://mcp.scalekit.com/surveymonkeymcp",
"headers": {"Authorization": "Bearer " + token}
}
})
tools = await mcp.get_tools()
import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "surveymonkeymcp" });

const openai = new OpenAI();
// Connect to MCP at https://mcp.scalekit.com/surveymonkeymcp
// Pass: Authorization: Bearer + token
import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "surveymonkeymcp" });

const anthropic = new Anthropic();
// Connect to MCP at https://mcp.scalekit.com/surveymonkeymcp
// Pass: Authorization: Bearer + token
from google.adk.agents import LlmAgent
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="surveymonkeymcp")
# Connect to MCP at https://mcp.scalekit.com/surveymonkeymcp
# Pass: Authorization: Bearer + token
Try these prompts
Paste any prompt into your agent to get started.
Get started
Copy the prompt
Copied
Update survey properties such as title or nickname?
Copy the prompt
Copied
Get a paginated list of surveys for the authenticated user?
Advanced
Copy the prompt
Copied
Bulk reorder all questions on a survey page?
Copy the prompt
Copied
Get details about a specific survey including title, dates, language, and question count?
SEE HOW AUTH WORKS
User authorises once. Every agent call after uses their token with scope enforcement.
1
Authorize
Your user connects
SurveyMonkey MCP
once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access
Who:
user ‘A’
when:
Once per user
access:
Limited to user
2
Store
Their
SurveyMonkey MCP
token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection
vault:
encrypted
scope:
per-user
tokens:
auto-refreshed
3
Resolve
When your agent calls a
SurveyMonkey MCP
tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs
speed:
~40ms
check:
before every call
seen by:
nobody
4
Audit
Every
SurveyMonkey MCP
tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it
history:
90 days
export:
SIEM-ready
logged:
every call
Test other agents
See the same per-user auth pattern across other connectors.
SALES
Deal intelligence agent
Combine Gong, Attio, and Slack signals to surface deal risks and next-best actions. Updated after every call.
ENGINEERING
Engineering standup agent
Aggregate GitHub and GitLab activity, link to Jira, and post a daily standup digest to Slack. No async updates.
Why Scalekit
Secure your agent's access. Connectors ship in minutes
Other connector libraries treat auth as a demo afterthought.
01.
Shared tokens break per-user analytics
A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential.
// shared token
audit → bot_service_account

// scalekit
audit → user_abc ✓
02.
Authentication is not authorization
03.
Multi-tenancy is architectural
04.
One connector today. Ten tomorrow.
“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”
Venu Madhav Kattagoni
Head of Engineering / Von
FAQs
Frequently Asked Questions

Does the agent access SurveyMonkey as the user or as a shared key?
As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.

Where is the SurveyMonkey OAuth token stored?
In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.

Can I limit what the agent is allowed to do in SurveyMonkey?
Yes. Pass a tool name filter to listScopedTools so the analytics agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches SurveyMonkey.

What happens when a user revokes SurveyMonkey access?
The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

Can the agent edit live surveys or only drafts?
Whatever the authorizing user can do in SurveyMonkey. Question edits and collector changes follow the user's seat and team role, and you can filter to response-read tools for analysis-only agents.

Start in your coding agent
Up and running in one command
Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up
Claude Code REPL
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""surveymonkeymcp"": {
""url"": ""https://mcp.scalekit.com/surveymonkeymcp"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.surveymonkeymcp]
url = ""https://mcp.scalekit.com/surveymonkeymcp""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""surveymonkeymcp"": {
""url"": ""https://mcp.scalekit.com/surveymonkeymcp"",
""type"": ""http""
}
}
}