Qualitative Researcher MCP Server

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