Knowledge Graph Causal Discovery

Example Use Cases

• 1

  Discover and analyze causal relationships in complex multi-source datasets.

• 2

  Extract and embed causal knowledge from academic literature and knowledge graphs.

• 3

  Estimate causal effects and simulate counterfactual scenarios for research or decision-making.

Description

This MCP server provides eight specialized tools for discovering causal structures, computing interventional effects, simulating counterfactuals, extracting causal claims from literature, embedding causal knowledge graphs, estimating causal effects, checking graph consistency, and attributing data source contributions. It enables comprehensive causal analysis and entity resolution from diverse data sources, supporting research and AI applications. The server requires an Apify API token and operates on a pay-per-use pricing model via the Apify platform.