Qualitative Researcher MCP Server

A sophisticated tool for retrieving rich, contextual information about qualitative research entities, providing structured insights tailored to different research components.

When to use this tool:

• Retrieving detailed information about research projects, participants, interviews, and analytical elements
• Exploring thematic analyses and research findings
• Reviewing participant profiles and interview transcripts
• Examining code definitions and their connections to data
• Analyzing emerging themes and their supporting evidence
• Investigating research questions and related findings
• Reviewing analytical memos and their connections to data
• Preparing for coding sessions by establishing contextual understanding
• Exploring relationships between codes, themes, and concepts
• Getting a comprehensive overview of project progress and insights
• Tracking research activities by their current status
• Managing tasks based on their assigned priorities
• Understanding sequential relationships between research processes

Key features:

• Provides richly formatted, context-aware information about research entities
• Adapts output format based on entity type (project, participant, interview, code, theme, memo, researchQuestion)
• Presents both direct entity information and related research elements
• Shows research design, methodology, and analysis progression
• Tracks entity views within the current research session
• Formats information in a structured, readable markdown format
• Highlights relationships between research elements
• Presents supporting quotes and evidence for themes and codes
• Shows co-occurrence patterns between codes where available
• Includes status information for tracking research progress
• Displays priority assignments for critical research elements
• Visualizes sequential relationships between research processes

Parameters explained:

1. entityName: Required - The name of the entity to retrieve context for

• Example: "Health Behavior Study", "Participant_P001", "Interview_20230315"

2. entityType: Optional - The type of entity being retrieved

• Default: "project"
• Helps the system format the output appropriately
• Common types include: "project", "participant", "interview", "code", "theme", "memo", "researchQuestion", "status", "priority"

3. sessionId: Optional - The current session identifier

• Typically provided by startsession
• Used for tracking entity views within the session

Each entity type returns specialized context information:

• Project: Shows project status, description, research design, research questions, data collection stats, recent interviews, analysis progress (themes), and findings
• Participant: Displays demographic information, interview history, observation records, notable quotes, and research memos
• Interview: Shows project affiliation, participant, date, transcript content, applied codes, and notable quotes
• Code: Displays definition, status, creation date, code group affiliations, supporting quotes, sources, associated themes, and code co-occurrence data
• Theme: Shows description, status, creation date, project affiliation, supporting codes, example quotes, and analytical memos
• Memo: Displays topic, date, project affiliation, content, and related entities
• Research Question: Shows the question text, project affiliation, related findings, themes, and supporting quotes
• Status: Shows all entities assigned this status value, organized by entity type
• Priority: Shows all entities assigned this priority value, organized by entity type
• Other Entity Types: Shows observations and relationship information for other entity types

Status and Priority Information:

• All entity displays include status information when available via has_status relations
• Priority assignments are shown for tasks and other prioritized elements
• Valid status values include: planning, data_collection, analysis, writing, complete, scheduled, conducted, transcribed, coded, analyzed, emerging, developing, established, preliminary, draft, final, active, in_progress
• Valid priority values include: high, low

Sequential Process Relationships:

• Entity displays show preceding and following entities through precedes relations
• Process sequences are visualized to show workflow between research activities
• Research phases and activities display their position in the overall research process

Return information:

• Formatted markdown text with hierarchical structure
• Sections adapted to the specific entity type
• Related entities shown with their descriptions and connections
• Status and priority information prominently displayed
• Sequential relationships clearly indicated
• Error messages if the entity doesn't exist or can't be retrieved

You should:

• Specify the exact entity name for accurate retrieval
• Provide the entity type when possible for optimally formatted results
• Start with project entities to get a high-level overview of research
• Use participant context to understand individual perspectives
• Examine interview context to see coding applied to raw data
• Review code context to understand analytical categories
• Explore theme context to see patterns and theoretical constructs
• Use research question context to track progress toward answering key inquiries
• Examine memo context to review analytical insights
• Check status entities to see all research elements at the same stage
• Review priority entities to identify critical research tasks
• Explore sequential relationships to understand research process flow
• After retrieving context, follow up on specific entities of interest
• Use in conjunction with startsession to maintain session tracking
• Remember that this tool only retrieves existing information; use buildcontext to add new entities

A multi-stage tool for documenting qualitative research sessions, recording analysis progress, tracking coding activities, and creating a structured record of research evolution.

When to use this tool:

• Concluding a qualitative research analysis session
• Documenting interview data collection activities
• Recording newly created analytical memos
• Tracking coding activities and code applications
• Documenting emerging themes and theoretical constructs
• Updating overall project status and progress
• Creating a structured record of research activities
• Establishing a formal conclusion to a focused research period
• Building a historical record of project development
• Documenting observations and insights from a research session
• Updating status values for research activities and entities
• Assigning or modifying priority levels for research tasks
• Establishing or modifying sequential relationships between research processes

Key features:

• Provides a structured, multi-stage workflow for research session documentation
• Records interview data collection in the knowledge graph
• Captures newly created analytical memos
• Tracks coding activities across data sources
• Documents emerging themes and their connections to codes
• Updates project status information
• Maintains session continuity with unique session IDs
• Supports revision of previous stages when needed
• Offers a comprehensive assembly stage that consolidates all session information
• Organizes qualitative research activity into a coherent narrative
• Manages status progression of research activities
• Tracks priority assignments for research tasks
• Documents sequential relationships between research processes

The endsession tool uses a sequential, multi-stage approach with typically 8 stages:

1. Summary Stage: Records basic session information
2. Interview Data Stage: Documents new interviews conducted
3. Memos Stage: Records new analytical memos created
4. Coding Activity Stage: Documents code applications and coding work
5. Themes Stage: Records emerging themes and theoretical insights
6. Status Updates Stage: Records changes to entity status values
7. Project Status Stage: Updates the overall project status
8. Assembly Stage: Consolidates all information and finalizes the session record

Parameters explained:

1. sessionId: Required - Unique identifier for the research session

• Obtained from the startsession tool
• Example: "qual_1234567890_abc123"

2. stage: Required - Current stage of the endsession workflow

• Accepts: "summary", "interviewData", "memos", "codingActivity", "themes", "statusUpdates", "projectStatus", or "assembly"
• Each stage has specific data requirements and processing logic

3. stageNumber: Required - The sequence number of the current stage

• Starts at 1 and typically progresses through the stages
• Used to track progress through the session documentation workflow

4. totalStages: Required - Total number of stages planned for this workflow

• Typically 8 for the complete workflow
• Provides context for the progress within the overall process

5. analysis: Optional - Text analysis or observations for the current stage

• Descriptive text explaining the work done in this stage
• Example: "Analyzed interview transcripts and identified recurring patterns"

6. stageData: Optional - Stage-specific structured data

• Structure varies by stage type:
  • summary: { summary: "Session summary text", duration: "3 hours", project: "ProjectName" }
  • interviewData: { interviews: [{ participant: "P001", notes: "Interview notes", date: "2023-04-15" }] }
  • memos: { memos: [{ topic: "Emerging patterns", content: "Detailed memo text" }] }
  • codingActivity: { codes: [{ code: "coping_strategy", dataItem: "Interview_P001", note: "Applied to discussion of stress management" }] }
  • themes: { themes: [{ name: "Social Support", codes: ["family_support", "peer_networks"], description: "The role of social connections in coping" }] }
  • statusUpdates: { statusUpdates: [{ entityName: "Interview_P003", newStatus: "transcribed", note: "Completed transcription" }, { entityName: "Code_Resilience", newStatus: "established", note: "Well-supported by data" }] }
  • projectStatus: { projectStatus: "data_analysis", projectObservation: "Making good progress on initial coding", priorityUpdates: [{ entityName: "Transcribe_P004", priority: "high", note: "Critical for thematic development" }], sequenceUpdates: [{ before: "Coding_Phase1", after: "Theme_Development", note: "Ready to move from coding to theme creation" }] }
  • assembly: No stageData needed - automatically assembled from previous stages

7. nextStageNeeded: Required - Whether additional stages are needed after this one

• Boolean value (true/false)
• Set to false on the final stage to complete the session

8. isRevision: Optional - Whether this is revising a previous stage

• Boolean value (true/false)
• Default: false

9. revisesStage: Optional - If revising, which stage number is being revised

• Required when isRevision is true
• Indicates which previous stage is being updated

Status and Priority Management:

• The statusUpdates stage allows for batch updates to entity status values
• Valid status values include: planning, data_collection, analysis, writing, complete, scheduled, conducted, transcribed, coded, analyzed, emerging, developing, established, preliminary, draft, final, active, in_progress
• Priority assignments (high, low) can be modified in the projectStatus stage
• Status changes are tracked to maintain a history of research progression
• Priority changes help reallocate focus as research needs evolve

Sequential Process Management:

• The projectStatus stage allows for defining or modifying sequential relationships
• The precedes relation is used to establish logical ordering between research activities
• Sequential updates help maintain a coherent research workflow
• Process sequences can be visualized through the loadcontext tool

When the endsession workflow completes (assembly stage with nextStageNeeded: false), the tool:

1. Records the session completion in persistent storage
2. Creates a formatted summary of all session information
3. Updates the status, priority, and sequential relationships for relevant entities
4. Preserves the record of research activities for future reference

Return information:

• JSON response with the following structure:
  • success: Boolean indicating whether the operation succeeded
  • stageCompleted: The stage that was just completed
  • nextStageNeeded: Whether more stages are required
  • stageResult: The processed result of the current stage
  • endSessionArgs: (Only in assembly stage) Consolidated arguments for the session
  • sessionRecorded: (Final stage only) Whether the session was recorded
  • summaryMessage: (Final stage only) Formatted summary of all recorded information
  • error: (Only on failure) Error message describing the issue

You should:

• Complete all stages in order for comprehensive session documentation
• Provide specific details in each stage for accurate research documentation
• Document interview data with participant identifiers and key notes
• Create descriptive titles for analytical memos
• Be specific about which codes were applied to which data items
• Connect emerging themes to their supporting codes
• Update status values to reflect progress in research activities
• Assign appropriate priorities to focus attention on critical tasks
• Define logical sequences between research processes with precedes relations
• Include relevant observations for project status updates
• If making a revision, specify which stage is being revised
• Only mark nextStageNeeded as false on the final assembly stage
• Review the final summary message to confirm all session details were recorded properly
• Use the unique session ID consistently across all stages

A comprehensive tool for initializing a new qualitative research session, providing structured information about ongoing research projects, participants, analytical elements, and recent research activities.

When to use this tool:

• Beginning a new research analysis session
• Getting oriented to your current research state across multiple projects
• Planning which research elements to focus on in the current session
• Reviewing recent research activities and progress
• Identifying active research projects and their status
• Exploring available participants for analysis
• Reviewing your most frequently used codes
• Accessing recent analytical memos
• Establishing research context before diving into specific analysis tasks
• Re-engaging with your research after time away
• Prioritizing high-priority research tasks
• Tracking the status of various research activities
• Understanding sequential research processes

Key features:

• Generates a unique session identifier for tracking research activities
• Retrieves and displays recent research sessions with summaries
• Lists active research projects with status and phase information
• Provides a sample of research participants with demographic information
• Presents your most frequently used codes with reference counts
• Highlights recent analytical memos with type and summary information
• Formats information in an easily scannable format for quick orientation
• Integrates with the loadcontext tool for deeper exploration
• Maintains continuity between research sessions
• Tracks research session history for progress review
• Displays high-priority research tasks needing attention
• Shows status information for key research activities
• Presents sequential relationships between research processes

Parameters explained: No parameters required - the tool automatically retrieves all relevant context.

Return information:

• A unique session identifier
• Recent research sessions (up to 3) with:
  • Date
  • Project name
  • Brief summary
• Active research projects with:
  • Project name
  • Current status
  • Research phase
• Sample participants (up to 5) with:
  • Participant name
  • Demographic information
  • Participation status
• Top codes (up to 10) with:
  • Code name
  • Reference count
  • Code group
• Recent memos (up to 3) with:
  • Memo name
  • Creation date
  • Memo type
  • Brief summary
• High-priority research tasks (up to 5) with:
  • Task name
  • Current status
  • Associated project
• Upcoming research activities (up to 3) with:
  • Activity name
  • Scheduled date
  • Prerequisite activities
  • Current status

Status and Priority Information:

• Research activities are displayed with their current status values
• High-priority tasks are prominently highlighted for attention
• Valid status values include: planning, data_collection, analysis, writing, complete, scheduled, conducted, transcribed, coded, analyzed, emerging, developing, established, preliminary, draft, final, active, in_progress
• Priority values (high, low) help indicate which tasks need immediate attention

Sequential Process Information:

• Upcoming activities show prerequisite tasks that must be completed first
• Research phases are presented in their logical sequence
• The precedes relation is used to determine activity ordering
• Sequential relationships help visualize the research workflow

Session Workflow:

1. Start a research session with startsession
2. Review the provided context to decide what to focus on
3. Use loadcontext to retrieve detailed information about specific research elements
4. Conduct your analysis, adding new elements with buildcontext as needed
5. End the session with endsession to record your research progress

You should:

• Begin each focused research period with startsession to establish context
• Review recent sessions to maintain continuity in your research
• Identify active projects that require attention
• Note available participants for interview analysis
• Consider frequently used codes that may indicate important patterns
• Review recent memos to reconnect with your analytical thinking
• Prioritize high-priority tasks for immediate attention
• Check the status of research activities to maintain progress awareness
• Consider sequential relationships when planning your research activities
• Use the session ID when using other tools to maintain session tracking
• After completing a session, record your progress using endsession
• Establish a regular cadence of research sessions to maintain momentum
• Use the structured overview to make deliberate choices about where to focus your analytical effort

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

A precise tool for removing elements from the qualitative research knowledge graph, enabling researchers to maintain data accuracy and refine their analytical framework.

When to use this tool:

• Removing incorrect or duplicate research entities
• Deleting erroneous relationships between research elements
• Clearing outdated observations from research entities
• Restructuring your research framework as analysis evolves
• Removing pilot or test data that shouldn't be included in final analysis
• Cleaning up the knowledge graph during research refinement phases
• Eliminating deprecated codes, themes, or concepts that no longer fit your analytical framework
• Removing sensitive information that should not be retained
• Reorganizing your analytical structure by removing and recreating elements
• Updating status assignments when research activities change state
• Modifying priority assignments as research focus shifts
• Restructuring sequential relationships between research processes

Key features:

• Provides targeted deletion capabilities for three distinct types of knowledge graph elements: entities, relations, and observations
• Maintains knowledge graph integrity during deletion operations
• Supports batch deletion of multiple items in a single operation
• Returns clear confirmation of deletion results
• Preserves the overall structure of the research knowledge graph while removing specific elements
• Performs validation to ensure deletion requests are properly formatted
• Handles status and priority relation management
• Supports modification of sequential process relationships

Parameters explained:

1. type: The type of deletion operation to perform

• Accepts: "entities", "relations", or "observations"
• Determines how the data parameter is interpreted

2. data: The elements to remove from the knowledge graph (structure varies by type):

• For "entities": Array of entity names to delete
  • Example: ["Participant_A", "Interview_3"]
• For "relations": Array of relation objects, each containing:
  • from: Name of the source entity
  • to: Name of the target entity
  • relationType: Type of relationship to remove (e.g., "participated_in", "codes", "has_status", "has_priority", "precedes")
• For "observations": Array of objects, each containing:
  • entityName: Name of the entity to remove observations from
  • indices: Array of numeric indices identifying which observations to remove

Deletion behavior by type:

• Entities: Removes the specified entities and all their associated relations from the knowledge graph
• Relations: Removes only the specified relationships, leaving the connected entities intact
• Observations: Removes specific observations from entities while preserving the entities themselves

Status and Priority Management:

• When deleting status or priority entities, be aware of the impact on entities that reference them
• For changing an entity's status or priority, first delete the existing has_status or has_priority relation, then create a new one
• Consider the research workflow implications when removing status entities or relations
• Deletion of a status entity will remove all has_status relations pointing to it

Sequential Process Management:

• Removing precedes relations affects the logical flow of research processes
• Consider restructuring sequential relationships after deletion to maintain process continuity
• When reorganizing research phases, update all affected precedes relations

Safety considerations:

• Entity deletion is permanent and will also remove all relationships involving those entities
• Consider exporting or backing up your research knowledge graph before performing large-scale deletions
• For sensitive operations, consider removing specific observations rather than entire entities
• When removing codes or themes, consider the impact on your analytical framework
• Status changes should be carefully managed to maintain accurate research progress tracking
• Changes to sequential relationships may affect dependent research activities

Return information:

• JSON response indicating success or failure
• For successful operations:
  • Success flag set to true
  • Confirmation message
• For failed operations:
  • Success flag set to false
  • Error message describing the issue

You should:

• Be specific in your deletion requests to avoid unintended data loss
• Use relations deletion when you want to disconnect entities without removing them
• For observations, provide the exact indices to ensure only the intended content is removed
• When restructuring your analysis, consider how deletions will affect related elements
• Use deletecontext in conjunction with buildcontext to refine and evolve your research framework
• Regularly review your knowledge graph for elements that may need to be removed or updated
• Consider the cascading effects of entity deletion on your overall research structure
• Use observation deletion for minor corrections rather than removing entire entities
• When updating entity status, delete the old has_status relation before creating a new one
• Maintain logical consistency when modifying sequential process relationships

A sophisticated query tool for exploring, analyzing, and retrieving complex information from the qualitative research knowledge graph.

When to use this tool:

• Retrieving a comprehensive view of your entire research knowledge structure
• Searching for specific research entities across your qualitative data corpus
• Getting detailed information about particular research projects, participants, or analytical elements
• Exploring relationships between research components (codes, themes, quotes)
• Analyzing code frequencies and distributions across your data
• Retrieving interview or observation transcripts for analysis
• Accessing memo content for reflection on the research process
• Generating codebooks or analytical frameworks for documentation
• Finding connections between different aspects of your research
• Creating research reports or summaries from your data
• Exploring thematic structures and their evidentiary basis
• Identifying entities by status to track research progress
• Filtering tasks by priority to manage research workflow
• Analyzing sequential relationships between research processes

Key features:

• Offers specialized operations for querying different aspects of qualitative research data
• Retrieves complete or filtered views of the research knowledge graph
• Provides flexible search capabilities across all research entities
• Supports detailed exploration of specific entities by name
• Generates specialized views for projects, participants, codes, and themes
• Retrieves content and metadata for interviews, transcripts, and memos
• Creates codebooks and thematic frameworks for documentation
• Identifies related entities to explore connections within your research
• Returns consistently structured JSON responses for easy processing
• Facilitates depth and breadth exploration of qualitative data
• Supports status-based filtering of research entities
• Enables priority-based task management
• Provides sequential process analysis capabilities

Parameters explained:

1. type: The type of query operation to perform

• Accepts one of the specialized operations: "graph", "search", "nodes", "project", "participant", "codes", "themes", "transcript", "memo", "analysis", "codebook", "related", "status", "priority", "sequence"
• Determines how the params parameter is interpreted

2. params: Operation-specific parameters (structure varies by type):

• For "graph": No parameters needed (retrieves the full research knowledge graph)
• For "search": Object containing:
  • query: Search string to find entities (supports entity type filters)
• For "nodes": Object containing:
  • names: Array of entity names to retrieve
• For "project": Object containing:
  • projectName: Name of the project to retrieve details for
• For "participant": Object containing:
  • participantName: Name of the participant to retrieve profile for
• For "codes": Object containing:
  • projectName: (Optional) Project name to filter codes by
• For "themes": Object containing:
  • projectName: (Optional) Project name to filter themes by
• For "transcript": Object containing:
  • participantName: Participant associated with the transcript
  • interviewId: (Optional) Specific interview identifier
• For "memo": Object containing:
  • memoName: Name of the memo to retrieve
• For "analysis": Object containing:
  • projectName: Project name to retrieve analysis artifacts for
• For "codebook": Object containing:
  • projectName: Project name to generate codebook for
• For "related": Object containing:
  • entityName: Name of the entity to find related entities for
• For "status": Object containing:
  • statusValue: The status value to filter by (e.g., "planning", "data_collection", "analysis")
• For "priority": Object containing:
  • priorityValue: The priority value to filter by (e.g., "high", "low")
• For "sequence": Object containing:
  • entityName: Name of the entity to find sequential relationships for

Operation details:

• graph: Returns the complete research knowledge graph with all entities and relationships
• search: Performs text-based search across entity names and observations
• nodes: Retrieves detailed information about specific entities by name
• project: Returns comprehensive project information including participants, interviews, codes, and findings
• participant: Generates a participant profile with demographic information and associated data
• codes: Lists all codes, optionally filtered by project, with reference counts and descriptions
• themes: Returns all themes, optionally filtered by project, with associated codes and descriptions
• transcript: Retrieves interview transcript content for specific participant/interview combinations
• memo: Returns the full content of an analytical memo with metadata
• analysis: Collects all analysis artifacts (codes, themes, memos) for a specific project
• codebook: Generates a structured codebook for a project with code definitions and examples
• related: Identifies all entities directly connected to a specific entity
• status: Retrieves all entities with a specific status value
• priority: Retrieves all entities with a specific priority value
• sequence: Identifies sequential relationships for a specific entity showing preceding and following entities

Status and Priority Information:

• Status queries return entities organized by their current research stage
• Priority queries help identify critical research tasks and elements
• Status values include: planning, data_collection, analysis, writing, complete, scheduled, conducted, transcribed, coded, analyzed, emerging, developing, established, preliminary, draft, final, active, in_progress
• Priority values include: high, low

Sequential Process Information:

• Sequence queries identify entities that come before or after in a research process
• Sequential relationships help visualize the research workflow
• The sequence operation shows both incoming and outgoing precedes relations

Return information:

• JSON response with a consistent structure:
  • success: Boolean indicating whether the operation succeeded
  • Additional fields depend on the operation type:
    • graph: Complete knowledge graph
    • results: For search operations
    • nodes: For specific entity retrieval
    • project/participant/etc.: For specialized views
    • status/priority: Lists of entities with specified status/priority values
    • sequence: Preceding and following entities in research processes
• Error information when operations fail

You should:

• Start with broad queries ("graph", "search") to explore your research corpus
• Use specific entity queries ("nodes", "project", "participant") for detailed information
• Combine search and related queries to discover connections in your data
• Generate codebooks and project overviews for documentation and reporting
• Use transcript retrieval to access primary data when needed
• Explore thematic structures through themes and related entity queries
• Review memos to track your analytical process over time
• Filter code and theme queries by project for more focused results
• Use search with entity type filters to find specific types of research elements
• Use status queries to identify all entities at a particular research stage
• Use priority queries to focus on high-priority research tasks
• Use sequence queries to understand process flows in your research methodology