@cyanheads/survey-mcp-server

@cyanheads/survey-mcp-server

Enables LLMs to conduct dynamic, conversational surveys with skip logic, session resume, and pluggable storage.

Category
Visit Server

README

<div align="center"> <h1>@cyanheads/survey-mcp-server</h1> <p><b>Transform LLMs into intelligent interviewers. A production-grade MCP server for conducting dynamic, conversational surveys with structured data collection. Features skip logic, session resume, multi-tenancy, and pluggable storage backends.</b></p> </div>

<div align="center">

Version MCP Spec MCP SDK License Status TypeScript Bun Code Coverage

</div>


šŸ› ļø Tools Overview

This server provides eight powerful tools for managing the complete survey lifecycle with LLM-driven interactions:

Tool Name Description
survey_list_available Discover available surveys in the definitions directory.
survey_start_session Initialize a new session with complete survey context, all questions, and initial suggested questions.
survey_get_question Refresh a specific question's eligibility status after state changes (useful for conditional logic).
survey_submit_response Record participant answers with validation, scoring, returning updated progress and next suggested questions.
survey_get_progress Check completion status, current score, remaining required/optional questions, and completion eligibility.
survey_complete_session Finalize a completed session with final score summary (requires all required questions answered).
survey_export_results Export session data in CSV or JSON format with optional filtering by status, date range, etc.
survey_resume_session Resume an incomplete session, restoring full context including answered questions and progress.

survey_list_available

Discover available surveys loaded from your survey definitions directory.

Key Features:

  • Lists all surveys discovered via recursive directory scan of SURVEY_DEFINITIONS_PATH
  • Returns survey metadata: ID, title, description, estimated duration, and question count
  • Optional tenant filtering for multi-tenant deployments

Example Use Cases:

  • "Show me all available surveys"
  • "What surveys can participants take?"
  • "List surveys for tenant X"

survey_start_session

Initialize a new survey session with complete context for LLM-driven conversations.

Key Features:

  • Creates new session with unique session ID and participant tracking
  • Loads complete survey definition with all questions upfront
  • Returns initial suggested questions based on survey settings (configurable min/max, defaults to 3-5) based on eligibility (unconditional questions first, required before optional)
  • Each question includes currentlyEligible flag and eligibilityReason for transparency
  • Provides guidanceForLLM field with conversational instructions
  • Supports session metadata for tracking source, user agent, etc.

Example Use Cases:

  • "Start the customer satisfaction survey for participant ABC123"
  • "Begin a new session for the Q1 feedback survey"
  • "Initialize survey session with metadata: source=web, userAgent=Claude"

survey_get_question

Refresh a question's eligibility and details after session state changes.

Key Features:

  • Returns current eligibility status based on latest session state
  • Provides eligibility reason (e.g., "Conditional logic satisfied", "Always available")
  • Indicates if question was already answered
  • Useful for checking if conditional questions became available after previous answers

Example Use Cases:

  • "Has question q2 become available yet?"
  • "Check if the follow-up question is now eligible"
  • "Refresh question details after the participant answered the dependency"

survey_submit_response

Record participant answers with validation and get dynamic response guidance.

Key Features:

  • Validates responses against question constraints (min/max length, patterns, required fields, etc.)
  • Calculates and returns score for response (if scoring is enabled on question options)
  • Returns validation errors with specific, actionable feedback
  • Updates session progress (percentage complete, questions answered, time remaining estimate, current score)
  • Returns updatedEligibility array showing newly available conditional questions
  • Provides refreshed nextSuggestedQuestions based on new state (count configurable per survey)
  • Includes guidanceForLLM with context-aware instructions

Example Use Cases:

  • "Submit answer 'very-satisfied' for question q1"
  • "Record the participant's email: user@example.com"
  • "Save free-form response with validation"

survey_get_progress

Check session status and completion eligibility.

Key Features:

  • Returns completion status: in-progress, completed, abandoned
  • Progress metrics: total questions, answered count, required remaining, percentage complete, current score
  • Lists all unanswered required questions (with eligibility status)
  • Lists all unanswered optional questions (with eligibility status)
  • canComplete boolean indicating if session can be finalized
  • completionBlockers array explaining what's preventing completion

Example Use Cases:

  • "How much of the survey is complete?"
  • "What required questions are still unanswered?"
  • "Can we complete the survey now?"

survey_complete_session

Finalize a completed session when all required questions have been answered.

Key Features:

  • Validates that all required questions (including conditionally required) are answered
  • Updates session status to completed and sets completedAt timestamp
  • Returns summary with total questions answered, session duration, and final score (if scoring enabled)
  • Prevents duplicate completion

Example Use Cases:

  • "Complete the survey session"
  • "Finalize session sess_abc123"
  • "Mark the survey as finished"

survey_export_results

Export session data for analysis and reporting.

Key Features:

  • Export in CSV or JSON format
  • Filter by survey ID, status, date range, and custom criteria
  • Returns formatted data with record count and generation timestamp
  • CSV format includes one row per session with flattened question responses
  • JSON format preserves full session structure

Example Use Cases:

  • "Export all completed responses for survey customer-satisfaction-q1-2025 as CSV"
  • "Get JSON export of sessions completed in January 2025"
  • "Export in-progress sessions for analysis"

survey_resume_session

Resume an incomplete session with full context restoration.

Key Features:

  • Restores complete survey context and session state
  • Returns all previously answered questions with responses
  • Provides refreshed nextSuggestedQuestions for remaining questions (count configurable per survey)
  • Shows elapsed time since last activity
  • Current progress summary (percentage, remaining questions, current score)
  • Includes guidanceForLLM with welcome-back messaging suggestions

Example Use Cases:

  • "Resume session sess_abc123"
  • "Continue the survey where the participant left off"
  • "Restore session state for participant to finish later"

✨ Features

This server is built on the mcp-ts-template and inherits its rich feature set:

  • Declarative Tools: Define capabilities in single, self-contained files. The framework handles registration, validation, and execution.
  • Robust Error Handling: A unified McpError system ensures consistent, structured error responses.
  • Pluggable Authentication: Secure your server with zero-fuss support for none, jwt, or oauth modes.
  • Abstracted Storage: Swap storage backends (in-memory, filesystem, Supabase, Cloudflare KV/R2) without changing business logic.
  • Full-Stack Observability: Deep insights with structured logging (Pino) and optional, auto-instrumented OpenTelemetry for traces and metrics.
  • Dependency Injection: Built with tsyringe for a clean, decoupled, and testable architecture.
  • Edge-Ready: Write code once and run it seamlessly on your local machine or at the edge on Cloudflare Workers.

Plus, specialized features for Survey Management:

  • LLM-Driven Surveys: Tools provide rich context (progress, next suggested questions, validation results, scores) to guide natural conversation flow.
  • Hybrid Flow Control: Guided mode with configurable suggested questions (defaults to 3-5) + flexible ordering based on conversation context.
  • Scoring System: Support for quizzes and assessments with optional score fields on question options. Automatic score calculation and accumulation per session.
  • Advanced Conditional Logic: Support for simple skip logic and complex AND/OR multi-condition branching with eligibility tracking.
  • JSON-Based Survey Definitions: Define surveys in simple JSON files with recursive directory scanning.
  • Multiple Question Types: free-form, multiple-choice, multiple-select, rating-scale, email, number, boolean, and advanced types like date, datetime, time, and matrix grids.
  • Validation Engine: Min/max length, patterns, required fields, custom constraints, and date/time rules with extensible validator map pattern.
  • Session Resume: Built-in state management allows participants to pause and continue later.
  • Help Text: A helpText field on questions provides LLMs with context and guidance for asking questions naturally.
  • Pagination Support: Scalable data retrieval with configurable pagination for session queries and exports.

šŸš€ Getting Started

MCP Client Settings/Configuration

Add the following to your MCP Client configuration file (e.g., cline_mcp_settings.json).

{
  "mcpServers": {
    "survey-mcp-server": {
      "command": "bunx",
      "args": ["@cyanheads/survey-mcp-server@latest"],
      "env": {
        "MCP_LOG_LEVEL": "info",
        "SURVEY_DEFINITIONS_PATH": "./survey-definitions",
        "SURVEY_RESPONSES_PATH": "./survey-responses"
      }
    }
  }
}

Prerequisites

Installation

  1. Clone the repository:
git clone https://github.com/cyanheads/survey-mcp-server.git
  1. Navigate into the directory:
cd survey-mcp-server
  1. Install dependencies:
bun install
  1. Explore example surveys: The survey-definitions/ directory contains example JSON files demonstrating various question types and features. Use these as a starting point for creating your own surveys.

šŸ› ļø Core Capabilities: Survey Tools

This server equips AI agents with specialized tools to conduct dynamic, conversational surveys while maintaining structured data collection.

Example Interaction Flow

1. LLM calls survey_start_session
   → Receives full survey context, all questions, and first 3-5 suggested questions

2. LLM asks questions naturally in conversation
   → Follows suggestions but can adapt order based on context
   → Uses natural language while ensuring survey questions are covered

3. For each answer, LLM calls survey_submit_response
   → Receives validation feedback (re-prompts if needed)
   → Gets score for response (if scoring enabled): "+5 points (Total: 45)"
   → Gets progress update (50% complete, 2 of 4 questions answered)
   → Refreshed suggestions with newly eligible conditional questions

4. LLM can check survey_get_progress anytime
   → Knows exactly what's required vs optional
   → Understands what remains before completion is possible

5. When all required questions answered, LLM calls survey_complete_session
   → Session finalized with timestamp, summary, and final score
   → Ready for export via survey_export_results

šŸ“– View detailed specification and examples →

āš™ļø Configuration

All configuration is centralized and validated at startup in src/config/index.ts. Key environment variables in your .env file include:

Variable Description Default
SURVEY_DEFINITIONS_PATH Path to directory containing survey JSON files (recursive scan). ./survey-definitions
SURVEY_RESPONSES_PATH Path to directory for storing session responses (filesystem mode). ./survey-responses
MCP_TRANSPORT_TYPE The transport to use: stdio or http. http
MCP_HTTP_PORT The port for the HTTP server. 3019
MCP_AUTH_MODE Authentication mode: none, jwt, or oauth. none
STORAGE_PROVIDER_TYPE Storage backend: in-memory, filesystem, supabase, cloudflare-kv, r2. in-memory
OTEL_ENABLED Set to true to enable OpenTelemetry. false
LOG_LEVEL The minimum level for logging (debug, info, warn, error). info
MCP_AUTH_SECRET_KEY Required for jwt auth. A 32+ character secret key. (none)
OAUTH_ISSUER_URL Required for oauth auth. URL of the OIDC provider. (none)

ā–¶ļø Running the Server

Local Development

  • Build and run the production version:

    # One-time build
    bun rebuild
    
    # Run the built server
    bun start:http
    # or
    bun start:stdio
    
  • Run checks and tests:

    bun devcheck # Lints, formats, type-checks, and more
    bun test # Runs the test suite
    

Cloudflare Workers

  1. Build the Worker bundle:
bun build:worker
  1. Run locally with Wrangler:
bun deploy:dev
  1. Deploy to Cloudflare:
    bun deploy:prod
    

šŸ“‚ Project Structure

Directory Purpose & Contents
survey-definitions/ Survey definitions (JSON files). Nested directories supported for organization.
survey-responses/ Session responses (when using filesystem provider). Organized by tenant ID.
src/mcp-server/tools Survey tool definitions (survey-*.tool.ts). 8 tools for complete lifecycle.
src/mcp-server/resources Resource definitions for survey metadata and discovery.
src/services/survey/ Survey service with filesystem provider for loading definitions.
src/mcp-server/transports Implementations for HTTP and STDIO transports, including auth middleware.
src/storage StorageService abstraction and all storage provider implementations.
src/container Dependency injection container registrations and tokens.
src/utils Core utilities for logging, error handling, performance, and security.
src/config Environment variable parsing and validation with Zod.
tests/ Unit and integration tests, mirroring the src/ directory structure.
docs/ Detailed specifications and guides (see survey-mcp-server-spec.md).

šŸ§‘ā€šŸ’» Agent Development Guide

For strict rules when using this server with an AI agent, refer to the .clinerules file (or AGENTS.md) in this repository. Key principles include:

  • Logic Throws, Handlers Catch: Never use try/catch in your tool logic. Throw an McpError instead.
  • Pass the Context: Always pass the RequestContext object through your call stack for logging and tracing.
  • Use the Barrel Exports: Register new tools and resources only in the index.ts barrel files within their respective definitions directories.

šŸ¤ Contributing

Issues and pull requests are welcome! If you plan to contribute, please run the local checks and tests before submitting your PR.

bun run devcheck
bun test

šŸ“œ License

This project is licensed under the Apache 2.0 License. See the LICENSE file for details.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured