Research Gap Analyzer MCP Server
Search and retrieve academic papers from the arXiv repository.
Utilizes Google Gemini as an LLM backend for generating summaries, research ideas, and evaluating novelty.
Search and retrieve academic papers and metadata from Semantic Scholar.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Research Gap Analyzer MCP Serverfind research gaps in few-shot learning for NLP"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Research Gap Analyzer MCP Server
An AI-powered Research Copilot that automates literature review, research gap detection, and novelty evaluation.
Features (9 Tools)
search_literature(topic): Search recent papers across arXiv and Semantic Scholar.
summarize_literature(topic): Extract methods, datasets, and limitations from literature.
find_gaps(topic): Identify overlooked research areas.
generate_ideas(topic): Propose novel FYP/research ideas.
find_datasets(topic): Extract dataset names, modalities, and usage details.
evaluate_novelty(idea): Semantic novelty score (0-10) using BGE embeddings.
suggest_venues(idea): Recommend target journals and conferences.
suggest_experiments(idea): Design experiments and suggest metrics.
create_literature_review(topic): Compile structured literature reviews.
Related MCP server: Research MCP
Installation
1. Clone & Setup
# Install dependencies
uv sync2. Configure Environment
Create a .env file:
GROQ_API_KEY=your_groq_key_here
GEMINI_API_KEY=your_gemini_key_here
SEMANTIC_SCHOLAR_API_KEY=optional_key_here3. Usage
Run the server locally:
uv run main.pyRemote Deployment (fastmcp.cloud)
Deploy to FastMCP Cloud
Push your code to GitHub
Go to fastmcp.cloud
Connect your GitHub repository
Configure environment variables in the fastmcp.cloud dashboard:
GROQ_API_KEYGEMINI_API_KEYSEMANTIC_SCHOLAR_API_KEY(optional)
Deploy - the platform will automatically detect and run your MCP server
Remote Claude Desktop Configuration
After deployment, update your claude_desktop_config.json to use the remote server:
{
"mcpServers": {
"research_analyzer": {
"url": "https://your-server-name.fastmcp.cloud"
}
}
}Replace your-server-name with your actual fastmcp.cloud server URL.
Claude Desktop Configuration
Add this to your claude_desktop_config.json:
{
"mcpServers": {
"research_analyzer": {
"command": "uv",
"args": [
"--directory",
"[YOUR_PROJECT_PATH]/research-gap-analyzer",
"run",
"main.py"
]
}
}
}Tech Stack
Framework: FastMCP
LLM: Groq (Llama 3.3 70B) & Google Gemini 2.0 Flash
Search: arXiv API, Semantic Scholar API
Embeddings: Sentence-Transformers (BAAI/bge-small-en-v1.5)
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