Semilattice - audience prediction

Test content, personalise features, and A/B test decisions with accurate audience prediction.

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What it can do

  • List Population Models: List all available population models. Returns: List of population model dictionaries, each containing an 'id' field that can be used with create_prediction()
  • Create Prediction: Predict how a population would answer a question. Args: population_id: The ID of the population model to use. Get valid IDs by calling list_population_models() question: The questio
  • Get Prediction: Retrieve a prediction by ID to check its status and results. Args: prediction_id: The ID of the prediction to retrieve. This is the 'id' field returned by create_prediction() Returns:

What data it sees

Do you need an account

No: the server works without sign-in

Test content, personalise features, and A/B test decisions with accurate audience prediction. Semilattice MCP lets agents predict things about your audience. Your agent could predict which email subject line or website copy your audience would prefer. Or it could predict which use cases your audience wants to see in a new product experience. Audience predictions are >87% accurate on average and take <20 seconds to complete.

How to connect

How to connect Semilattice - audience prediction to Claude

The server address to paste into Claude settings:

https://semilattice--semilattice.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect Semilattice - audience prediction to ChatGPT

The server address to paste into ChatGPT settings:

https://semilattice--semilattice.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect Semilattice - audience prediction to Cursor

The server address to paste into Cursor settings:

https://semilattice--semilattice.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (4)

Raw names from tools/list. Only developers need these.

list_population_modelsList all available population models. Returns: List of population model dictionaries, each containing an 'id' field that can be used with create_prediction()
create_predictionPredict how a population would answer a question. Args: population_id: The ID of the population model to use. Get valid IDs by calling list_population_models() question: The question to ask the population answer_options: List of possible answer choices question_type: Either "single-choice" or "multiple-choice" (default: "single-choice") Returns: Dictionary containing the prediction with an 'id' field (initially status will be "Queued"). Use the 'id' field with get_prediction() or wait_for_prediction() to check results.
get_predictionRetrieve a prediction by ID to check its status and results. Args: prediction_id: The ID of the prediction to retrieve. This is the 'id' field returned by create_prediction() Returns: Dictionary containing prediction status and results (if completed)
wait_for_predictionWait for a prediction to complete and return the results. Predictions typically take ~20 seconds to complete. Args: prediction_id: The ID of the prediction to wait for. This is the 'id' field returned by create_prediction() max_wait_seconds: Maximum time to wait in seconds (default: 60) Returns: Dictionary containing completed prediction results with 'predicted_answer_percentages'