Datapoint MCP
Enables AI agents to recruit real humans for evaluation tasks like surveys, A/B tests, and ratings on text, images, audio, and video, returning aggregated results directly into the conversation.
README
<!-- mcp-name: io.github.impel-intelligence/datapoint-mcp -->
Datapoint MCP
Get real human opinions from inside any MCP client. Run surveys, A/B preference comparisons, ratings, and rankings on text, images, audio, and video — without leaving your editor.
Datapoint MCP is an MCP server that gives Claude, GPT, Gemini, and any other MCP-capable agent the ability to recruit real humans for evaluation tasks, then return aggregated results back into the conversation. Built on top of Datapoint AI.
Why
LLMs are great at generating options and bad at telling you which one a real person will prefer. Datapoint MCP closes that loop — your agent can hand off to a panel of real humans and pick up the results a few minutes later.
Use cases
- Design & UX — A/B test logos, landing pages, screens, ad creative, copy
- AI evaluation — human ratings of model outputs, side-by-side comparisons, hallucination checks
- Preference data — collect RLHF / DPO pairs at scale
- Dataset labeling — classification, ranking, captioning, content moderation
- Product research — quick concept tests, naming, pricing reads
- Human-in-the-loop checks — gate an agent before it ships something irreversible
Tools
| Tool | Description |
|---|---|
setup |
Authenticate with your Datapoint AI account (opens browser) |
upload_media |
Upload local images, audio, or video so they can be used in a survey |
plan_survey |
Design a survey from a natural language description |
create_survey |
Launch a survey from a plan |
check_survey |
Check status, progress, and aggregated results |
get_survey_responses |
Get raw per-annotator responses (paginated) |
list_surveys |
List all your surveys |
pause_survey |
Pause task serving for an active survey (in-flight responses keep arriving) |
resume_survey |
Resume task serving for a paused survey |
cancel_survey |
Permanently cancel a survey and refund unused reserved credits (irreversible) |
check_balance |
Check your account balance |
add_credits |
Open a checkout link to top up your account |
Install
Requires uv on your PATH.
Claude Code
As a plugin (recommended):
/plugin marketplace add impel-intelligence/datapoint-mcp
/plugin install datapoint@datapoint
To pick up new versions: /plugin marketplace update datapoint then /plugin update datapoint@datapoint.
As a raw MCP server (in ~/.claude/settings.json):
{
"mcpServers": {
"datapoint": {
"command": "uvx",
"args": ["--from", "git+https://github.com/impel-intelligence/datapoint-mcp.git", "datapoint-mcp"]
}
}
}
Claude Desktop
Add to claude_desktop_config.json (~/Library/Application Support/Claude/ on macOS, %APPDATA%\Claude\ on Windows):
{
"mcpServers": {
"datapoint": {
"command": "uvx",
"args": ["--from", "git+https://github.com/impel-intelligence/datapoint-mcp.git", "datapoint-mcp"]
}
}
}
Restart Claude Desktop, then ask it to run setup.
Cursor
Add to ~/.cursor/mcp.json (or via Settings → MCP):
{
"mcpServers": {
"datapoint": {
"command": "uvx",
"args": ["--from", "git+https://github.com/impel-intelligence/datapoint-mcp.git", "datapoint-mcp"]
}
}
}
Windsurf
Add to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"datapoint": {
"command": "uvx",
"args": ["--from", "git+https://github.com/impel-intelligence/datapoint-mcp.git", "datapoint-mcp"]
}
}
}
VS Code (GitHub Copilot Chat / agent mode)
Add to your workspace .vscode/mcp.json:
{
"servers": {
"datapoint": {
"command": "uvx",
"args": ["--from", "git+https://github.com/impel-intelligence/datapoint-mcp.git", "datapoint-mcp"]
}
}
}
Any other MCP client
Run the binary over stdio:
uvx --from git+https://github.com/impel-intelligence/datapoint-mcp.git datapoint-mcp
Usage
Once installed, just ask:
"Survey 20 people: which logo do they prefer, A or B?"
"Get human ratings on these three model outputs — which sounds most natural?"
"Run a quick A/B test on these two landing-page headlines."
The agent calls plan_survey to design it, shows you the plan and cost, then calls create_survey to launch. Use check_survey to monitor progress and read aggregated results.
Run setup first to authenticate if you haven't already.
Chain surveys (multi-step flow)
Some surveys have dependent questions — the second only makes sense given a specific answer to the first. Describe it that way and Claude will plan a chain:
"Ask 20 listeners if they could understand the speaker in this clip. If yes, rate the audio quality 1–5. If not, skip the rating."
A chain ties 2–5 steps together into a single unit of annotator work: every step is served to the same annotator, in order, and a per-step skip_if rule can end the response early. Claude will show you the full chain structure (steps, any skip conditions, cost) and wait for your confirmation before calling create_survey.
The cost shown in plan_survey is the upper bound (every response answers every step); when skip_if rules fire, responses cost proportionally less.
Configuration
| Environment variable | Description |
|---|---|
DATAPOINT_API_KEY |
API key (overrides saved config) |
DATAPOINT_BASE_URL |
API base URL (default: https://api.trydatapoint.com/data-labelling/v1) |
How it compares
| Datapoint MCP | Mechanical Turk | Prolific | UserTesting | |
|---|---|---|---|---|
| Run from inside an AI agent / IDE | ✅ | ❌ | ❌ | ❌ |
| Designed for AI/LLM evaluation | ✅ | ⚠️ | ⚠️ | ❌ |
| Pay-as-you-go via API | ✅ | ✅ | ✅ | ❌ |
| Supports media (image / audio / video) | ✅ | ✅ | ✅ | ✅ |
| Minutes to first response | ✅ | ⚠️ | ⚠️ | ❌ |
Links
- Homepage: trydatapoint.com
- MCP spec: modelcontextprotocol.io
- Issues / discussions: GitHub
License
MIT — see LICENSE.
Recommended Servers
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.
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.
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.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
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.
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.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
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.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.