fastchat-mcp 1.0.0

Python client, based on fastmcp, for connecting to MCP servers through multiple protocols, specifically designed to work with integrated language models.

fastchat-mcp

Python client, based on "mcp[cli]", for connecting to MCP servers through multiple protocols, specifically designed to work with integrated language models.

Table of Contents

• Overview
• Installation
• LLM Implementation
  • LLM Providers
  • LLM Models
• Implemented Transfer Protocols
• System Requirements
• Usage Example
• Version History
• Project Status
• Flow
• License

Overview

This package provides a Python interface to connect to MCP servers in an easy, intuitive, and configurable way. It offers a modular architecture that allows for easy extension of new transfer protocols and language models. Currently includes support for HTTPStream and GPT-4 mini, with expansion capability for more options in the future.

Installation

To install the MCP client, you can use pip:

pip install fastchat-mcp

LLM Implementation

LLM Providers

The client currently supports the following language models:

Provider	Status	Technical Description
OpenAI	Implemented	OpenAI is a leading provider of artificial intelligence-based language models that develop advanced technologies for automatic text processing and generation through models like GPT.

🚨 CONFIGURATION NOTE Currently, this project only work with OpenAI llm provider.

Default Provider (OpenAI): OpenAI is a leading provider of artificial intelligence-based language models that develop advanced technologies for automatic text processing and generation through models like GPT.

LLM Models

This project can use any valid OpenAI language model, providing flexibility to choose the model that best fits your specific needs. To explore all available models, their features, and how to use them, it is recommended to consult the official OpenAI documentation.

To select a model, you should create a chat instance like this:

from fastchat import Chat
chat = Chat(model="my-openai-model-name", ...)

Default Model ("gpt4-o-mini"): gpt4-o-mini is an optimized implementation of the GPT-4 model that provides a balance between computational performance and resource efficiency. This model is specifically designed to operate in environments with memory constraints while maintaining superior predictive quality.

Implemented Transfer Protocols

Protocols for communication with MCP servers:

Protocol	Status	Technical Characteristics
stdio	Implemented	Standard input/output interface that facilitates direct communication between processes.
HTTPStream	Implemented	Asynchronous HTTP-based protocol that enables continuous data streaming.
SSE (Server-Sent Events)	Not Implemented	Unidirectional protocol that allows the server to send multiple updated events through a single HTTP connection.

🚨 CRITICAL CONFIGURATION NOTE Currently, this project don't work with SSE (Server-Sent Events) protocol.

System Requirements

Environmental Configuration

• .env file: The .env file contains the authentication credentials necessary for integration with external services. This file must be created in the project root directory with the following format:

  # .env
  
  #CRIPTOGRAFY_KEY by token data storage (OAuth2)
  CRIPTOGRAFY_KEY=<any-criptografy-key>
  
  # OpenAI Authentication
  OPENAI_API_KEY=<your-openai-key>
  

• fastchat.config.json file: The fastchat.config.json file defines the configuration of available MCP servers. It must be created in the project root directory with this structure

Dependencies

• Python = ">=3.11"
• openai = "^1.68.2"
• mcp[cli]
• mcp-oauth

File fastchat.config.json

This file defines the configuration of available MCP servers (Model Context Protocol) in the project. It must be placed in the root directory of the repository. Its main purpose is to inform the application which servers can be used and how to connect to them.

General Structure

The file is JSON formatted and follows this main structure:

{
    "app_name": "fastchat-mcp",
    "mcp_servers": {
    "..."
    }
}

• app_name: The identifiable name of the appslication or project using these MCP servers.
• mcp_servers: An object listing one or more configured MCP servers, each with its unique key.

Server Definition

Each MCP server inside "mcp_servers" has a custom configuration with these common properties:

• Server key (e.g., "example_public_server", "github", etc.): internal name identifying this server.

• protocol: Protocol or communication method. It can be:

  • "httpstream": Communication via HTTP streaming.
  • "stdio": Communication based on standard input/output (local command execution).

Server Configuration Examples

1. Public HTTP Stream Server

"example_public_server": {
    "protocol": "httpstream",
    "httpstream-url": "http://127.0.0.1:8000/public-example-server/mcp",
    "name": "example-public-server",
    "description": "Example public server."
}

• httpstream-url: Base URL where the MCP HTTP streaming server is exposed.
• No authentication required (public access).
• "name" and "description" provide descriptive labels for users.

2. Private HTTP Stream Server with Authentication

"example_private_mcp": {
    "protocol": "httpstream",
    "httpstream-url": "http://127.0.0.1:8000/private-example-server/mcp",
    "name": "example-private-server",
    "description": "Example private server with oauth required.",
    "auth": {
        "required": true,
        "post_body": {
            "username": "user",
            "password": "password"
        }
    }
}

• Adds an "auth" object on top of basic config:
  • required: true indicates authentication is needed.
  • post_body: Data sent for authentication (username and password here).
• Suitable for servers secured with OAuth2.

3. GitHub Server with Authentication Headers

"github": {
    "protocol": "httpstream",
    "httpstream-url": "https://api.githubcopilot.com/mcp",
    "name": "github",
    "description": "This server specializes in github operations.",
    "headers": {
        "Authorization": "Bearer {your-github-access-token}"
    }
}

• Uses a custom HTTP header "Authorization" for token-based authentication.
• Perfect for sending API keys or tokens in headers to access the server.

4. Local Server using STDIO protocol

"my-stdio-server": {
    "protocol": "stdio",
    "name": "my-stdio-server",
    "config": {
        "command": "npx",
        "args": [
            "-y",
            "@modelcontextprotocol/example-stdio-server"
        ]
    }
}

• Does not use HTTP; communication happens by executing local commands.
• "config" specifies the command and arguments to run the MCP server. This key value(or body) has the same Claude Desktop sintaxis.
• Useful for local integrations or development testing without networking.

Notes

see config.example.json

⚠️ Place this file in the project root so the application can detect it automatically.

💡 If you need an httpstream MCP server to test the code, you can use simple-mcp-server.

✍️ If you need help configuring a specific server or using this configuration in your code, feel free to open discussion for help!

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Usage Example

#example1.py
from fastchat import open_local_chat
open_local_chat()

https://github.com/user-attachments/assets/1fcb0db8-5798-4745-8711-4b93198e36cc

#example2.py
from fastchat import Chat
chat: Chat = Chat()
while True:
    query = input("> ")
    if query == "":
        break
    for step in chat(query):
        print(f"<< {step.json}")

Alternatively, you may test this service using the following template available on GitHub:

# clone repo
git clone https://github.com/rb58853/template-fastchat-mcp.git
# change to project dir
cd template-fastchat-mcp
# install dependencies
pip install -r requirements.txt
# open in vscode
code .

Version History

Last Version Features

• 💬 Fully functional streaming chat by passing a query; see Chat.
• ⚙️ Integration with Tools, Resources, and Prompts from MCP servers, achieving a well-integrated client workflow with each of these services. Check flow
• 🔐 Simple authentication system using mcp-oauth and this environmental configuration. Also integrate headers authorization.
• 👾 OpenAI GPT as an integrated LLM using any valid OpenAI language model.
• 📡 Support for the httpstream protocol protocol.
• 📟 Support for the stdio protocol protocol.
• 💻 Easy console usage via open_local_chat(); see example1 for the use case.

See more in changelog

Project Status

⚠️ Important Notice: This project is currently in active development phase. As a result, errors or unexpected behaviors may occur during usage

License

MIT License. See license

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