What is Mcp Chatbot

mcp-chatbot is a modular, asynchronous research assistant that integrates Anthropic Claude 3 with the Model Context Protocol (MCP). It provides on-demand literature search and summarization services tailored for academics and engineers.

Use cases

Use cases for mcp-chatbot include conducting literature reviews for research projects, summarizing academic papers for easier comprehension, and providing quick answers to specific queries related to various topics in academia and engineering.

How to use

To use mcp-chatbot, clone the repository from GitHub, install the necessary dependencies, and either run it using Docker or locally. You can interact with the chatbot through a command-line interface (CLI) or a REPL mode.

Key features

Key features of mcp-chatbot include integration with Anthropic Claude 3 for advanced natural language processing, support for literature search and summarization, a modular architecture for easy customization, and a command-line interface for user interaction.

Where to use

mcp-chatbot is primarily used in academic and engineering fields where literature review and summarization are essential. It can assist researchers, students, and professionals in quickly accessing and understanding relevant literature.

mcp-chatbot

A modular, async research assistant that combines Anthropic Claude 3 with the Model Context Protocol (MCP), delivering on‐demand literature search and summarisation for academics and engineers.

1. Project Structure

mcp-chatbot/
├── Dockerfile
├── pyproject.toml
├── uv.lock
├── README.md
├── server_config.json
├── research_server.py
├── papers/                  # Cached paper metadata by topic
├── mcp_chatbot/
│   ├── __init__.py
│   ├── cli.py               # Typer-based CLI
│   └── core.py              # Main chatbot engine
└── tests/
    └── test_core.py

2. Quick Start

2.1. Clone the Repository

git clone https://github.com/mctrinh/mcp-chatbot.git
cd mcp-chatbot

2.2. Install Dependencies

Install uv (recommended)

# Git Bash or WSL on Windows, doesn't work in standard Command Prompt or PowerShell
curl -LsSf https://astral.sh/uv/install.sh | sh

# Scoop (Windows)
scoop install uv

# Chocolatey (Windows - Administrator Command Prompt - Recommended)
choco install uv
uv --version

Install Python packages in project.dependencies in pyproject.toml

pip install -e .

3. Build and Run with Docker

# Build image
docker build -t mcp-chatbot:0.1 .

# Run server and CLI (ports 8001 and 8000)
docker run --rm -it -p 8001:8001 -p 8000:8000 mcp-chatbot:0.1

4. Run Without Docker (Local Dev)

# Install dependencies
uv pip install -e .[dev]

# Start the research server (MCP tool)
python research_server.py

# In a new terminal, launch the chatbot CLI
mcp-chatbot run

5. Try the Chatbot

5.1. REPL Mode

python -m mcp_chatbot.cli run

Or using the installed script:

mcp-chatbot run

Once inside the REPL (Read-Eval-Print Loop), you can interact with the chatbot directly by typing commands or queries. Example commands:

/prompts            # list Claude prompts
@folders            # list downloaded paper topics
AI alignment        # ask anything – Claude decide whether to invoke tools

5.2. One-shot Query

mcp-chatbot once "What are the latest trends in diffusion models?"

6. Configuration (Optional)

Environment variables and server_config.json control model and ports:

export ANTHROPIC_MODEL="claude-3-opus-20240229"
export RESEARCH_PORT=8001
export PAPER_DIR=./papers

7. Testing

# Installs pytest, coverage, etc.
uv pip install -e .[dev]

# Run unit tests
pytest -q

# With coverage (optional)
pytest --cov=mcp_chatbot

8. Road map

• Research MCP server with search_papers and extract_info (done)

• Tool usage via Claude 3 (done)

• Prompt orchestration (done)

• Vector search over stored papers (Faiss / Chroma)

• Web UI using FastAPI + React

• GitHub Actions for CI/CD

9. License

MIT License. Copyright © 2025.

10. Current Issues

Issues occur when running mcp-chatbot run

• ⚠ Could not connect to server ‘fetch’: Method not found
• ⚠ Could not connect to server ‘filesystem’: Method not found