MCP_Based_AI_Assistant

An AI assistant built using Model Context Protocol (MCP) and LangGraph. The assistant can understand user queries, determine whether a tool is required, and invoke the appropriate MCP tool through an MCP client.

• MCP server with multiple tools

• MCP client for connecting to the MCP server

• MCP tool discovery

• LangGraph-based stateful agent workflow

• LLM-based tool selection

• Conditional tool execution

• Human-in-the-Loop approval for sensitive tools

• Document search

• Employee information lookup

• Mathematical expression calculation

• LLM-based final response generation

• Test cases for validating different queries and tool workflows

Architecture

Related MCP server: Enterprise Architecture MCP Server

Installation

1. Clone the repository

git clone <your-repository-url>
cd MCP_Based_AI_Assistant

2. Create a virtual environment

uv venv

3. Activate the virtual environment

Windows PowerShell

.venv\Scripts\Activate.ps1

4. Install dependencies

uv sync

5. Configure environment variables

Create a .env file in the project root directory:

GEMINI_API_KEY=your_gemini_api_key

6. Run the test cases

uv run python -m tests.test