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CogniResearch

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An MCP server for academic research combining local document search with Semantic Scholar API integration.

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Описание

An MCP server for academic research combining local document search with Semantic Scholar API integration.

README

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.

from github.com/marceliogreen/cogniresearch-mcp

Установка CogniResearch

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/marceliogreen/cogniresearch-mcp

FAQ

CogniResearch MCP бесплатный?

Да, CogniResearch MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для CogniResearch?

Нет, CogniResearch работает без API-ключей и переменных окружения.

CogniResearch — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить CogniResearch в Claude Desktop, Claude Code или Cursor?

Открой CogniResearch на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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