quantitativeresearch
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An MCP server implementation that provides tools for managing quantitative research knowledge graphs, enabling structured representation of research projects, datasets, variables, hypotheses, statistical tests, models, and results.
The Quantitative Researcher MCP Server is designed to assist researchers in organizing and managing their quantitative research projects through a structured knowledge graph. It allows for the persistent tracking of research entities such as projects, datasets, variables, and hypotheses, and supports the documentation of statistical analyses, model performance, and research findings. The server facilitates the management of research sessions, enabling researchers to maintain continuity across multiple analyses, document methodological decisions, and generate insights from numerical data. By linking data analyses to specific research questions and visualizing results, the server aids in the interpretation and reporting of research findings. It also supports the prioritization and sequencing of research tasks, ensuring methodological rigor and efficient project management.
Features
- Persistent Research Context: Maintain a structured knowledge graph of research entities and relationships across multiple analysis sessions
- Study Session Management: Track research analysis sessions with unique IDs and record progress over time
- Hypothesis Testing: Track hypotheses, their associated tests, and resulting conclusions
- Dataset Management: Organize and track descriptive statistics and variables within datasets
- Statistical Analysis: Record statistical tests, models, and their results
Tools
startsession
Launch a new quantitative research session
loadcontext
Loading a detailed context for a specific entity
endsession
Record research session results
buildcontext
Create new entities, relationships, or observations in the knowledge graph
deletecontext
Delete entities, relationships, or observations from knowledge graphs
advancedcontext
Search information from the knowledge graph
