Skip to main content

MCP server for survey collection with LLM-powered intelligent follow-up questions

Project description

Survey Collector MCP Server

PyPI version Python 3.10+ License: MIT

MCP server for survey collection with LLM-powered intelligent follow-up questions.

Features

  • 📋 Survey Collection: Send questions to groups and collect replies
  • 🤖 LLM-powered Follow-up: Automatically generate follow-up questions based on replies
  • 📊 Criteria Evaluation: Multiple evaluation criteria (all replied, majority agree, etc.)
  • 📝 Summary Reports: Auto-generate Markdown summary reports

Installation

Via pip

pip install survey-collector-mcp

Via uvx (recommended)

uvx survey-collector-mcp

Upgrade to latest version

pip install --upgrade survey-collector-mcp
# or
uvx --upgrade survey-collector-mcp

Usage

Local Mode (stdio)

Add to your mcp.json:

{
  "mcpServers": {
    "survey-collector": {
      "command": "uvx",
      "args": ["survey-collector-mcp"]
    }
  }
}

Remote Mode (SSE)

Start the server:

survey-collector --transport sse --host 0.0.0.0 --port 8001

Client configuration:

{
  "mcpServers": {
    "survey-collector": {
      "url": "http://localhost:8001/sse"
    }
  }
}

Tools

collect_survey_info

Execute a complete survey workflow with intelligent follow-up.

Parameters:

Parameter Type Required Description
chat_id string Yes Group chat ID
members string Yes Member names, comma-separated
question string Yes Survey question
criteria string No Evaluation criteria (default: all_replied)
follow_up_rule string No Follow-up rule in natural language
max_rounds int No Max follow-up rounds (default: 5)
timeout_per_round int No Timeout per round in seconds (default: 600)

Example:

Question: "周一上午有没有时间打球?"
Follow-up rule: "如果对方说没时间,每次追问日期往后推一天"

Result:
- Round 1: "周一上午有没有时间打球?"
- Round 2: "周二上午有没有时间打球?" (LLM generated)
- Round 3: "周三上午有没有时间打球?"

Configuration

Set environment variables or create .env file:

# HITL Platform
HITL_SERVICE_URL=https://hitl.woa.com/api

# LLM API (for intelligent follow-up)
LLM_API_BASE=https://api.deepseek.com/v1
LLM_API_KEY=your-api-key
LLM_MODEL=deepseek-chat

# Debug mode
DEBUG=false

📚 Documentation

License

MIT License

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

survey_collector_mcp-0.1.2.tar.gz (20.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

survey_collector_mcp-0.1.2-py3-none-any.whl (20.7 kB view details)

Uploaded Python 3

File details

Details for the file survey_collector_mcp-0.1.2.tar.gz.

File metadata

  • Download URL: survey_collector_mcp-0.1.2.tar.gz
  • Upload date:
  • Size: 20.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.6

File hashes

Hashes for survey_collector_mcp-0.1.2.tar.gz
Algorithm Hash digest
SHA256 94539fa17730ac2899c8bf63d633bba2d5333bafde478fa345dd6879e2795f77
MD5 5d4bdba6a53265622a2954630bafdd63
BLAKE2b-256 e91a90d44e38e64a705396c7fa450a2b67db182744c2e422e3a0950f5f9952af

See more details on using hashes here.

File details

Details for the file survey_collector_mcp-0.1.2-py3-none-any.whl.

File metadata

File hashes

Hashes for survey_collector_mcp-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 96b43d0ad3b6287f501ab47c1bebb9d947541b335c928938a65b6d6417c212ce
MD5 2a3be781132492a41a0b1448c57035ab
BLAKE2b-256 d7ab3061891a7a807c1c7645bb86d2dc1de259384c48c3418b42fd5b62f26d28

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page