RehanMohammed985/mcp-causal-inference-server
3.2
If you are the rightful owner of mcp-causal-inference-server and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.
The MCP Causal Inference Server is a Python-based server that performs causal inference analysis on synthetic customer spending data using DoWhy and FastMCP frameworks.
Tools
Functions exposed to the LLM to take actions
get_causal_estimate
Estimates causal effect using backdoor methods.
query_relationship
Checks if a causal relationship is identifiable using backdoor/frontdoor/IV.
get_variable_descriptions
Returns descriptions of the available dataset variables.
Prompts
Interactive templates invoked by user choice
No prompts
Resources
Contextual data attached and managed by the client