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Qualitative Researcher MCP Server

by tejpalvirk
qualitativeresearch_buildcontext.txt6.22 kB
A versatile tool for constructing and enhancing the qualitative research knowledge graph by adding new research elements, relationships, and observations. When to use this tool: - Creating new research entities (projects, participants, interviews, observations, codes, themes, memos, etc.) - Establishing relationships between research elements (e.g., connecting participants to projects, codes to data segments) - Adding observations, notes, or content to existing research entities - Building the research corpus incrementally as data collection and analysis progress - Organizing and structuring qualitative data within your research framework - Documenting emerging themes, codes, and analytical insights during research - Creating research questions and linking them to findings - Building code hierarchies and thematic frameworks - Setting status values for research activities and entities - Assigning priorities to research tasks and activities - Defining sequential relationships between research processes Key features: - Creates three distinct types of knowledge graph elements: entities, relations, and observations - Supports specialized qualitative research entity types (projects, participants, interviews, observations, documents, codes, etc.) - Validates entity and relation types against predefined standards for the qualitative research domain - Handles batch creation of multiple entities or relations in a single operation - Returns confirmation with details of created elements - Ensures proper data typing and structure for the qualitative research knowledge graph - Enables comprehensive documentation of the research process - Supports status and priority assignment through entity-relation model - Enables sequential relationships through precedes relation Parameters explained: 1. type: The type of creation operation to perform - Accepts: "entities", "relations", or "observations" - Determines how the data parameter is interpreted 2. data: The content to add to the knowledge graph (structure varies by type): - For "entities": An array of objects, each containing: * name: Unique identifier for the entity * entityType: One of the valid entity types (project, participant, interview, observation, document, code, codeGroup, memo, theme, quote, literature, researchQuestion, finding, status, priority) * observations: Array of strings containing notes or properties about the entity - For "relations": An array of objects, each containing: * from: Name of the source entity * to: Name of the target entity * relationType: The type of relationship between entities (e.g., "participated_in", "codes", "has_status", "has_priority") - For "observations": Either a single object or an array of objects, each containing: * entityName: Name of the entity to add observations to * contents: Array of strings with new observations to add Valid entity types: - project: Overall research study - participant: Research subjects - interview: Formal conversation with participants - observation: Field notes from observational research - document: External materials being analyzed - code: Labels applied to data segments - codeGroup: Categories or families of related codes - memo: Researcher's analytical notes - theme: Emergent patterns across data - quote: Notable excerpts from data sources - literature: Academic sources - researchQuestion: Formal questions guiding the study - finding: Results or conclusions - status: Entity status values - priority: Entity priority values Valid relation types: - participated_in: Links participants to interviews/observations - codes: Shows which codes apply to which data - contains: Hierarchical relationship - supports: Data supporting a theme or finding - contradicts: Data contradicting a theme or finding - answers: Data addressing a research question - cites: References to literature - followed_by: Temporal sequence - related_to: General connection - reflects_on: Memo reflecting on data/code/theme - compares: Comparative relationship - has_status: Links entity to its status - has_priority: Links entity to its priority - precedes: Entity comes before another entity in sequence Status information: - Valid status values include: planning, data_collection, analysis, writing, complete, scheduled, conducted, transcribed, coded, analyzed, emerging, developing, established, preliminary, draft, final, active, in_progress - Status is assigned through the has_status relation type Priority information: - Valid priority values: high, low - Priority is assigned through the has_priority relation type Return information: - JSON response indicating success or failure - For successful operations: * Success flag set to true * Details of created elements in the "created" field (for entities/relations) or "added" field (for observations) - For failed operations: * Success flag set to false * Error message describing the issue Error handling: - Validates entity types against the predefined list for qualitative research - Validates relation types against acceptable standards - Returns descriptive error messages for invalid inputs - Gracefully handles type mismatches and formatting errors You should: - Use consistent naming conventions for entities to facilitate relationships and retrieval - Begin by creating projects and participants before more specific research elements - Add detailed observations to entities to enhance context and retrievability - Create relationships to build a comprehensive network of interconnected research data - Use has_status relations to track the progress of research activities - Use has_priority relations to indicate important research elements - Use the precedes relation to establish sequences in research processes - Use observations to document the evolution of codes, themes, and analytical thinking - Regularly update entity observations as your understanding evolves - Build hierarchical structures using relations (e.g., codes within code groups, themes connecting multiple codes) - Document the full research journey by adding memos tied to specific analytical moments - Link quotes to codes, themes, and findings to maintain evidential chains

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