What is Mcp Chat Project

mcp-chat-project is a chat application designed for real-time communication, leveraging the capabilities of the MCP Server to facilitate seamless interactions among users.

Use cases

Use cases for mcp-chat-project include providing customer service through live chat, facilitating team discussions in remote work environments, enabling in-game communication among players, and creating community forums.

How to use

To use mcp-chat-project, users need to set up the MCP Server, clone the project repository, install the necessary dependencies, and run the application. Users can then connect to the server and start chatting.

Key features

Key features of mcp-chat-project include real-time messaging, user authentication, message history, and support for multiple chat rooms.

Where to use

mcp-chat-project can be used in various fields such as customer support, team collaboration, online gaming, and social networking.

mcp-chat-project

MCP Chat Project is an end-to-end conversational AI platform that lets teams spin up production-grade chat assistants quickly, then plug them into any product or workflow.

Goal- Deliver fast, context-aware conversations that feel natural and solve real world problems.
Tech Stack-
Backend: FastAPI · LangChain (LLM orchestration) · PostgreSQL · Redis
Frontend- Next.js · React · Tailwind · Chakra UI
Messaging- WebSocket + Server Sent Events for low-latency streaming
ML- OpenAI / Ollama-compatible adapters, custom fine-tuned models, Whisper ASR, AWS Polly TTS
Core Features - Multi-channel (web, Slack, WhatsApp)

• Retrieval Augmented Generation (RAG) with vector stores
• Voice in / voice out
• Session memory and user profiles
• Admin dashboard with analytics and feedback loop
  Target Users- Product teams that need rapid Q&A bots, campus help desks, healthcare triage flows, and hobby projects that want an LLM back end without the heavy lifting.

1 · Why it exists
Chatbots usually hit one of two walls: they are either too shallow (scripted flows) or too heavy (complex infra). MCP Chat Project fills the middle lane — opinionated defaults, but every layer is hackable.

2 · High-level architecture
lua
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Client (Next.js) <——WebSocket——> Gateway (FastAPI)
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±-----------±------------+
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RAG Service LLM Service
(vector store, (OpenAI, local
doc loaders) GGUF models)
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PostgreSQL + Redis Task Queue
Events stream from the gateway to the UI so tokens appear as soon as the model generates them.

A lightweight plugin system lets you inject custom tools — SQL queries, Python snippets, GraphQL calls — straight into the prompt chain.

Setup in three steps

git clone https://github.com/your-org/mcp-chat-project
cd mcp-chat-project
docker compose up --build
The stack boots with demo endpoints, an in-memory vector store, and a playground UI at localhost:3000.