mandoline-ai/mandoline-mcp-server
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Mandoline MCP Server enables AI assistants to evaluate and improve their performance using the Model Context Protocol.
Tools
Functions exposed to the LLM to take actions
create_metric
Define custom evaluation criteria for your specific tasks
batch_create_metrics
Create multiple evaluation metrics in one operation
get_metric
Retrieve details about a specific metric
get_metrics
Browse your metrics with filtering and pagination
update_metric
Modify existing metric definitions
create_evaluation
Score prompt/response pairs against your metrics
batch_create_evaluations
Evaluate the same content against multiple metrics
get_evaluation
Retrieve evaluation results and scores
get_evaluations
Browse evaluation history with filtering and pagination
update_evaluation
Add metadata or context to evaluations
Prompts
Interactive templates invoked by user choice
No prompts
Resources
Contextual data attached and managed by the client