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Research Kit
What is Research Kit
Research Kit is a Model Context Protocol (MCP) server that enhances AI model capabilities by integrating with various development tools and services, acting as a bridge between AI models and essential development services like Jira, Confluence, and GitLab.
Use cases
Use cases include automating issue tracking in Jira, managing documentation in Confluence, and facilitating version control operations in GitLab through natural language commands.
How to use
To use Research Kit, install it via Go, configure your environment variables in a .env file, and set up your AI model’s configuration to point to the Research Kit server.
Key features
Key features include structured and secure interaction between AI models and development tools, automation of development workflows, management of documentation, and handling version control operations through natural language.
Where to use
Research Kit can be used in software development, project management, and any field that requires integration of AI capabilities with development tools.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Research Kit
Research Kit is a Model Context Protocol (MCP) server that enhances AI model capabilities by integrating with various development tools and services, acting as a bridge between AI models and essential development services like Jira, Confluence, and GitLab.
Use cases
Use cases include automating issue tracking in Jira, managing documentation in Confluence, and facilitating version control operations in GitLab through natural language commands.
How to use
To use Research Kit, install it via Go, configure your environment variables in a .env file, and set up your AI model’s configuration to point to the Research Kit server.
Key features
Key features include structured and secure interaction between AI models and development tools, automation of development workflows, management of documentation, and handling version control operations through natural language.
Where to use
Research Kit can be used in software development, project management, and any field that requires integration of AI capabilities with development tools.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
Research Kit - Model Context Protocol (MCP) Server
Research Kit is a powerful Model Context Protocol (MCP) server designed to enhance AI model capabilities by providing seamless integration with various development tools and services. It serves as a bridge between AI models (like Claude) and essential development services such as Jira, Confluence, and GitLab.
Overview
This server implements the Model Context Protocol, allowing AI models to interact with development tools in a structured and secure way. It’s particularly useful for automating development workflows, managing documentation, and handling version control operations through natural language interactions.
Prerequisites
- Go 1.23.2 or higher
- Various API keys and tokens for the services you want to use
Installation
Installing via Go
- Install the server:
go install github.com/nguyenvanduocit/research-kit@latest
- Create a
.envfile with your configuration:
# Required for AI services DEEPSEEK_API_KEY= # Your Deepseek API key for advanced reasoning capabilities GOOGLE_AI_API_KEY= # Your Google AI API key for Gemini services # Optional configurations ENABLE_TOOLS= # Comma-separated list of tool groups to enable (empty = all enabled) PROXY_URL= # Optional: HTTP/HTTPS proxy URL if needed
- Config your claude’s config:
{ "mcpServers": { "research_kit": { "command": "research-kit", "args": ["-env", "/path/to/.env"], } } }
Enable Tools
There are a hidden variable ENABLE_TOOLS in the environment variable. It is a comma separated list of tools group to enable. If not set, all tools will be enabled. Leave it empty to enable all tools.
Available Tools
Group: deepseek
deepseek_reasoning
advanced reasoning engine using Deepseek’s AI capabilities for multi-step problem solving, critical analysis, and strategic decision support
Group: gemini
gemini_thinking
Use Gemini to think about a question. Gemini will provide a detailed answer to the question.
Group: sequentialthinking
sequentialthinking
`A detailed tool for dynamic and reflective problem-solving through thoughts.
This tool helps analyze problems through a flexible thinking process that can adapt and evolve.
Each thought can build on, question, or revise previous insights as understanding deepens.
When to use this tool:
- Breaking down complex problems into steps
- Planning and design with room for revision
- Analysis that might need course correction
- Problems where the full scope might not be clear initially
- Problems that require a multi-step solution
- Tasks that need to maintain context over multiple steps
- Situations where irrelevant information needs to be filtered out
Key features:
- You can adjust total_thoughts up or down as you progress
- You can question or revise previous thoughts
- You can add more thoughts even after reaching what seemed like the end
- You can express uncertainty and explore alternative approaches
- Not every thought needs to build linearly - you can branch or backtrack
- Generates a solution hypothesis
- Verifies the hypothesis based on the Chain of Thought steps
- Repeats the process until satisfied
- Provides a correct answer
Parameters explained:
- thought: Your current thinking step, which can include:
- Regular analytical steps
- Revisions of previous thoughts
- Questions about previous decisions
- Realizations about needing more analysis
- Changes in approach
- Hypothesis generation
- Hypothesis verification
- next_thought_needed: True if you need more thinking, even if at what seemed like the end
- thought_number: Current number in sequence (can go beyond initial total if needed)
- total_thoughts: Current estimate of thoughts needed (can be adjusted up/down)
- is_revision: A boolean indicating if this thought revises previous thinking
- revises_thought: If is_revision is true, which thought number is being reconsidered
- branch_from_thought: If branching, which thought number is the branching point
- branch_id: Identifier for the current branch (if any)
- needs_more_thoughts: If reaching end but realizing more thoughts needed
You should:
- Start with an initial estimate of needed thoughts, but be ready to adjust
- Feel free to question or revise previous thoughts
- Don’t hesitate to add more thoughts if needed, even at the “end”
- Express uncertainty when present
- Mark thoughts that revise previous thinking or branch into new paths
- Ignore information that is irrelevant to the current step
- Generate a solution hypothesis when appropriate
- Verify the hypothesis based on the Chain of Thought steps
- Repeat the process until satisfied with the solution
- Provide a single, ideally correct answer as the final output
- Only set next_thought_needed to false when truly done and a satisfactory answer is reached`
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










