CogniResearch

CogniResearch

An MCP (Model Context Protocol) server for academic research combining local document search with Semantic Scholar API integration.

Features

• Local RAG: Semantic search over your research documents using sentence transformers and ChromaDB
• Semantic Scholar API: Search academic literature with paper details, abstracts, and citations
• Configurable Personas: Three system prompt variants for different research workflows
• Claude Code Integration: Works as an MCP server within Claude Code

Installation

# Clone and navigate to project
cd cogniresearch-mcp

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# (Optional) Set your Semantic Scholar API key for higher rate limits
cp .env.example .env
# Edit .env and add your API key

Usage

Register with Claude Code

claude mcp add cogniresearch -- python -m cogniresearch.server

Or add to your Claude Code .mcp.json:

{
  "mcpServers": {
    "cogniresearch": {
      "command": "python",
      "args": ["-m", "cogniresearch.server"],
      "cwd": "/path/to/cogniresearch-mcp"
    }
  }
}

Available Tools

| Tool | Description | |------|-------------| | search_papers | Search Semantic Scholar for academic papers | | get_paper_details | Get detailed information about a specific paper | | search_library | Semantic search over your local documents | | get_context | Retrieve formatted context for a topic | | list_personas | List available system prompt personas | | set_persona | Switch between personas (default, critical, synthesis) |

Indexing Documents

Place your documents in the ./documents directory (supported formats: .md, .txt, .pdf).

The first search will automatically build the vector index.

Project Structure

cogniresearch-mcp/
├── cogniresearch/
│   ├── __init__.py           # Package init
│   ├── server.py             # MCP server with tool definitions
│   ├── config.py             # Configuration management
│   ├── rag.py                # Local RAG implementation
│   └── semantic_scholar.py   # Semantic Scholar API client
├── config/
│   └── prompts.yaml          # System prompt personas
├── tests/
│   └── test_server.py        # Basic tests
├── requirements.txt          # Python dependencies
└── README.md                 # This file

Personas

Default (Academic Research Assistant)

General literature search and citation management with professional, precise tone.

Critical (Methodology Reviewer)

Adversarial evaluation of research design and statistical validity.

Synthesis (Thesis Writing Assistant)

Helps integrate sources into academic prose with proper citation formatting.

Requirements

• Python 3.9+
• See requirements.txt for full dependencies

License

MIT License - see LICENSE file for details.