Tax Alert Chatbot MCP Server
Manages environment variables for API keys and database configuration
Powers the AI reasoning capabilities using Gemini 1.5 Flash and Pro models for the conversational interface
Provides the foundation for connecting to language models and structuring agent interactions
Implements the REACT-style reasoning agent framework for processing user queries and determining appropriate actions
Enables storage and retrieval of tax alert data with tools for querying, inserting, updating, and deleting records
Powers the interactive frontend chat interface that connects to the MCP server
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
π Tax Alert Chatbot (MCP-Powered)
An interactive Streamlit-based chatbot that connects to a custom MCP (Model Context Protocol) server. It allows users to query, insert, update, and delete tax alerts stored in a local SQLite database. The app uses LangGraphβs REACT agent framework with Google Gemini models and supports both SSE and STDIO transport modes.
π Project Structure
.
βββ client.py # Frontend Streamlit Chat UI
βββ server.py # MCP tool & Backend FastMCP SQLite server
βββ dummy_tax_alerts.db # SQLite database (if present)
βββ .env # Environment variables
βββ.venv # virtual environment
βββ README.md # Documentation
Related MCP server: MCP SQLite Demo
π Features
π€ Conversational interface with Google Gemini 1.5 models
π§ REACT-style reasoning agent via LangGraph
π οΈ Tool execution via MCP server
π Query, insert, update, and delete operations on tax alert data
π Real-time responses using SSE or STDIO
π οΈ Tech Stack
Layer | Tools / Frameworks |
Frontend | Streamlit, LangGraph, LangChain |
Backend | FastMCP, SQLite |
LLM Provider | Google Gemini 1.5 Flash / Pro (via LangChain) |
Transport | SSE (Server-Sent Events) or STDIO |
Runtime | Python 3.10+, venv, python-dotenv |
βοΈ Setup Instructions
1. Clone the Repository
git clone https://github.com/your-repo/tax-alert-chatbot.git
cd tax-alert-chatbot2. Create and Activate Virtual Environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate3. Install Dependencies
pip install -r requirements.txt
(Optional: Split into client/requirements.txt and server/requirements.txt if needed.)4. Configure Environment Variables
Create a .env file in the root folder:
GOOGLE_API_KEY=your_google_api_key
ALERTS_DB=dummy_tax_alerts.dbποΈ SQLite Schema
CREATE TABLE tax_alerts (
id INTEGER PRIMARY KEY AUTOINCREMENT,
title TEXT,
date TEXT,
jurisdiction TEXT,
topics TEXT,
summary TEXT,
full_text TEXT,
source_url TEXT,
tags TEXT,
created_at TIMESTAMP,
updated_at TIMESTAMP
);π§ MCP Server Tools
Tool Name | Description |
| Run |
| Insert a new tax alert into the database |
| Update existing tax alerts based on a condition |
| Delete tax alerts using |
| Return schema and column info of the table |
βΆοΈ Running the Server
python server.pyor
python server.py --transport stdioMake sure your .env contains a valid path to dummy_tax_alerts.db.
π¬ Running the Client (Chat UI)
streamlit run client.pyIt will automatically open streamlit localhost:8501 in your browser.
βοΈ Configuration (via Sidebar) Gemini Model: Choose between gemini-1.5-flash or gemini-1.5-pro
Server Mode: Only single server supported
Server Type: SSE or STDIO
Server URL: Required only for SSE mode
Clear Chat / Show Tool Executions: Debug & reset tools
π§ͺ Sample Interaction
User Input:
"Show me tax alerts from 2024 in California"Agent Response (Tool Call):
SELECT * FROM tax_alerts WHERE jurisdiction='California' AND date LIKE '2024%'π§Ό Debugging & Notes MCP server must be running before starting the client.
Full traceback is shown in the client if errors occur.
Ensure correct database path in .env.
This server cannot be deployed
Maintenance
Related MCP Connectors
Text-to-SQL MCP server: read-only queries on PostgreSQL, MySQL and SQL Server with your real schema
Xata MCP server lets AI agents interact with your Xata projects, and Postgres database branches.
MCP server unifying ERPs, CRMs, APIs and knowledge base for Claude, ChatGPT and Gemini.
Related MCP Servers
- AlicenseNot gradedqualityFmaintenanceA Model Context Protocol server that enables LLMs to interact with Ramp's financial data by retrieving, analyzing, and running tasks through Ramp's Developer API, using an in-memory SQLite database to overcome token limitations.34MIT
- FlicenseNot gradedqualityDmaintenanceA server that exposes SQLite database operations as tools, allowing natural language interactions with a database through LlamaIndex and Ollama LLM integration.1-
- FlicenseNot gradedqualityDmaintenanceA Model Context Protocol server that provides financial tools for retrieving real-time stock data, analyst recommendations, financial statements, and web search capabilities for a LangGraph-powered ReAct agent.1-
- FlicenseBqualityDmaintenanceA powerful SQLite-backed expense tracking server built with the Model Context Protocol (MCP). This server allows AI agents (like Claude) to manage your personal finances by adding, deleting, and listing expenses directly from your chat interface.3-