Qualitative Researcher MCP Server

An MCP server implementation that provides tools for managing qualitative research knowledge graphs, enabling structured representation of research projects, participants, interviews, observations, codes, themes, and findings. This server helps qualitative researchers organize their data, track their analysis process, develop themes, and generate insights from rich textual data.

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
- Thematic Analysis: Organize and track emergent themes across data sources
- Coding Framework: Manage hierarchical coding structures and track code applications
- Participant Management: Track participant data, demographics, and contributions
- Data Source Organization: Organize interviews, observations, and documents
- Research Question Tracking: Link data to specific research questions
- Memo Writing: Document analytical insights throughout the research process
- Chronological Data Analysis: Explore data in temporal sequence
- Code Co-occurrence Analysis: Identify relationships between different codes
- Methodology Documentation: Track methodological decisions and approaches

Entities

The Qualitative Researcher MCP Server recognizes the following 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 (active, completed, pending, abandoned)
- priority: Priority level values (high, low)

Relationships

Entities can be connected through the following relationship types:

- participated_in: Links participants to interviews/observations
- codes: Shows which codes apply to which data
- contains: Hierarchical relationship (e.g., codegroup contains codes)
- 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
- conducted_by: Person who conducted data collection
- transcribed_by: Person who transcribed data
- part_of: Entity is part of another entity
- derived_from: Entity is derived from another entity
- collected_on: Data collection date
- analyzes: Analysis relationship
- triangulates_with: Triangulation between data sources
- has_status: Links entities to their current status (active, completed, pending, abandoned)
- has_priority: Links entities to their priority level (high, low)
- precedes: Indicates that one analysis activity comes before another in a sequence

Available Tools

The Qualitative Researcher MCP Server provides these tools for interacting with research knowledge:

$3

Starts a new qualitative research session, generating a unique session ID and displaying current research projects, recent data collection, emergent themes, and previous sessions. Shows status information via has_status relations, priority levels via has_priority relations, and identifies research activities ready to be worked on next based on sequential process relationships.

$3

Loads detailed context for a specific entity (project, participant, interview, etc.), displaying relevant information based on entity type. Includes status information, priority levels, and sequential process relationships.

$3

Records the results of a research session through a structured, multi-stage process:
1. summary: Records session summary, duration, and project focus
2. interviewData: Documents new interview data processed during the session
3. memos: Records analytical memos created during the session
4. codingActivity: Tracks new and revised codes applied to data
5. themes: Documents emergent or developed themes from analysis
6. statusUpdates: Records changes to entity status values
7. projectStatus: Updates overall project status, priority assignments, and sequential relationships
8. assembly: Final assembly of all session data

$3

Creates new entities, relations, or observations in the knowledge graph:
- entities: Add new research entities (projects, participants, interviews, status, priority, etc.)
- relations: Create relationships between entities (including has_status, has_priority, precedes)
- observations: Add observations to existing entities

$3

Removes entities, relations, or observations from the knowledge graph:
- entities: Remove research entities
- relations: Remove relationships between entities (including status, priority, and sequential relations)
- observations: Remove specific observations from entities

$3

Retrieves information from the knowledge graph:
- graph: Get the entire knowledge graph
- search: Search for nodes based on query criteria
- nodes: Get specific nodes by name
- related: Find related entities
- status: Find entities with a specific status value (active, completed, pending, abandoned)
- priority: Find entities with a specific priority value (high, low)
- sequence: Identify sequential relationships for analysis activities

Domain-Specific Functions

The Qualitative Researcher MCP Server includes specialized domain functions for qualitative research:

- getProjectOverview: Comprehensive view of a project including research questions, methodology, participants, data sources
- getParticipantProfile: Detailed profile of a participant including demographics, interviews, and quotes
- getThematicAnalysis: Analysis of themes with supporting codes and data
- getCodedData: View all data segments tagged with a specific code
- getResearchQuestionAnalysis: Organize data by research questions with related findings
- getChronologicalData: View data in temporal sequence
- getCodeCooccurrence: Analyze where multiple codes appear together
- getMemosByFocus: Retrieve all memos related to a specific entity
- getMethodologyDetails: Review methodological approach, sampling, and analysis techniques
- getRelatedEntities: Find entities related to a specific entity by relationship type
- getStatusOverview: View all entities with a specific status (active, completed, pending, abandoned)
- getPriorityItems: Identify high-priority research tasks and activities
- getAnalysisSequence: Visualize the sequence of analysis activities based on precedes relations

Example Prompts

$3

``
Let's start a new qualitative research session for my Health Behavior Study project.
`

$3

`
Load the context for the Health Behavior Study project so I can see the current state of my analysis.
`

$3

`
I've just finished analyzing interview data for my Health Behavior Study. I identified two new themes related to social support, coded three new interviews, and wrote memos about emerging patterns in participant responses. I've marked the initial coding phase as complete and set the thematic analysis as high priority. The project is progressing well, and I'm beginning to reach theoretical saturation.
`

$3

`
Create a new code called "Family Support" that's part of the "Social Support" code group in the Health Behavior Study project. Set its status to active and make it precede the "Social Network Analysis" activity.
`

`
Update the status of the "Participant Recruitment" process to "completed" and add an observation that we've reached our target sample size.
`

Usage

This MCP server enables qualitative researchers to:

- Maintain Analytical Continuity: Keep track of analysis progress across multiple research sessions
- Develop Coding Frameworks: Build, refine, and apply coding structures to qualitative data
- Track Thematic Development: Observe how themes emerge and evolve during analysis
- Manage Rich Data Sources: Organize and connect interview transcripts, field notes, and documents
- Support Theoretical Development: Document theoretical insights through the memo writing process
- Prepare Research Findings: Connect findings to supporting evidence and research questions
- Enhance Methodological Rigor: Document methodological decisions and analysis process
- Track Research Progress: Monitor entity status throughout the research lifecycle
- Prioritize Research Tasks: Identify and focus on high-priority research activities
- Sequence Analysis Activities: Plan and visualize the logical order of research and analytical steps

Configuration

$3

Add this to your claude_desktop_config.json:

#### Install from GitHub and run with npx

`json
{
"mcpServers": {
"qualitativeresearch": {
"command": "npx",
"args": [
"-y",
"github:tejpalvirk/qualitativeresearch"
]
}
}
}
`

#### Install globally and run directly

First, install the package globally:

`bash
npm install -g github:tejpalvirk/qualitativeresearch
`

Then configure Claude Desktop:

`json
{
"mcpServers": {
"qualitativeresearch": {
"command": "contextmanager-qualitativeresearch"
}
}
}
`

#### docker

`json
{
"mcpServers": {
"qualitativeresearch": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"mcp/qualitativeresearch"
]
}
}
}
`

Building

$3

`bash


Clone the repository

git clone https://github.com/tejpalvirk/contextmanager.git
cd contextmanager

Install dependencies

npm install

Build the server

npm run build

Run the server

cd qualitativeresearch
node qualitativeresearch_index.js
`

$3

`bash
docker build -t mcp/qualitativeresearch -f qualitativeresearch/Dockerfile .
`

License

This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

Environment Variables

The Qualitative Research MCP Server supports the following environment variables to customize where data is stored:

- MEMORY_FILE_PATH: Path where the knowledge graph data will be stored
- Can be absolute or relative (relative paths use current working directory)
- Default: ./qualitativeresearch/memory.json

- SESSIONS_FILE_PATH: Path where session data will be stored
- Can be absolute or relative (relative paths use current working directory)
- Default: ./qualitativeresearch/sessions.json

Example usage:

`bash


Store data in the current directory

MEMORY_FILE_PATH="./qualitative-memory.json" SESSIONS_FILE_PATH="./qualitative-sessions.json" npx github:tejpalvirk/contextmanager-qualitativeresearch

Store data in a specific location (absolute path)

MEMORY_FILE_PATH="/path/to/data/qualitative-memory.json" npx github:tejpalvirk/contextmanager-qualitativeresearch

Store data in user's home directory

MEMORY_FILE_PATH="$HOME/contextmanager/qualitative-memory.json" npx github:tejpalvirk/contextmanager-qualitativeresearch
``