Flask-MCP-Plus
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Flask-MCP-PlusCreate a tool to add two integers"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Flask-MCP-Plus
Flask integration for Model Context Protocol (MCP) - a framework for building MCP servers with Flask.
Overview
Flask-MCP-Plus provides a simple and intuitive way to create Model Context Protocol (MCP) servers using Flask. It allows developers to easily expose tools, resources, and prompts that can be consumed by MCP clients, facilitating rich interactions between language models and external systems.
Related MCP server: Awesome MCP FastAPI
Features
Easy Integration: Seamless integration with Flask applications
Type Safety: Built-in support for type hints and Pydantic validation
Tool Support: Define MCP tools with automatic schema generation
Resource Management: Handle static and dynamic resources with URI templates
Prompt Generation: Create dynamic prompts for AI models
JSON Schema Generation: Automatic generation of JSON schemas from Python functions
Streaming Support: Streamable HTTP responses for large data
Installation
pip install flask-mcp-plusQuick Start
Here's a basic example to get you started:
from flask import Flask
from flask_mcp_plus import MCP
app = Flask(__name__)
mcp = MCP()
mcp.init_app(app, "my_mcp_server", __name__)
# Define a simple tool
@mcp.tool
def add(a: int, b: int) -> int:
"""Add two numbers together."""
return a + b
# Define a resource
@mcp.resource("http://example.com/data.json")
def get_data():
"""Return some static data."""
return {"message": "Hello, MCP!"}
# Define a prompt
@mcp.prompt
def greeting(name: str) -> str:
"""Create a personalized greeting."""
return f"Hello, {name}!"
if __name__ == "__main__":
app.run(debug=True)Use in Client
To use your Flask-MCP-Plus server with an MCP client, you need to configure the client to connect to your server's
endpoint.
The configuration format varies depending on the specific MCP client you're using, but generally follows this structure:
{
"mcpServers": {
"my_mcp_server": {
"autoApprove": [],
"disabled": false,
"timeout": 60,
"type": "streamableHttp",
"url": "http://127.0.0.1:5000/mcp"
}
}
}Core Concepts
Tools
Tools are functions that can be called by MCP clients. They can accept parameters and return structured results.
from flask_mcp_plus import Text, Field
from typing import Annotated
@mcp.tool(
name="calculate_sum",
title="Calculate Sum",
description="Add two floating point numbers",
icons=[
{
"src": "https://example.com/calculator-icon.png",
"mimeType": "image/png",
"sizes": ["48x48"]
}
]
)
def add_float(a: Annotated[float, Field(description="The first number")],
b: Annotated[float, Field(description="The second number")]) -> Text:
return Text(text=str(a + b))Resources
Resources provide data that can be fetched by URI. Flask-MCP-Plus supports both static URIs and dynamic URI templates with parameters.
@mcp.resource("file://data/config.json")
def get_config():
"""Return static configuration data."""
return {"setting1": "value1", "setting2": "value2"}
# Dynamic resource with path parameters
@mcp.resource("file://data/users/{user_id}.json")
def get_user(user_id: str):
"""Return user data by ID."""
return {"id": user_id, "name": f"User {user_id}"}Prompts
Prompts are specialized functions that return structured content to guide AI models.
from flask_mcp_plus import Message, Text
@mcp.prompt
def daily_fact() -> Message:
"""Return a daily fact as a message."""
return Message(
content=Text(text="The capital of France is Paris.")
)Advanced Usage
Custom Output Schema
For tools that return structured data, you can specify a custom JSON schema:
@mcp.tool(
output_schema={
"type": "object",
"properties": {
"result": {"type": "string"},
"success": {"type": "boolean"}
},
"required": ["result", "success"]
}
)
def api_call():
return {
"result": "Operation completed successfully",
"success": True
}Multiple Content Types
Tools can return multiple content types in a single response:
from flask_mcp_plus import Image, Text
@mcp.tool
def multi_data():
return [
Image(data=base64_image_data),
Text(text="Here's an image and some text")
]Running the Examples
The repository includes comprehensive examples in the src/example/ directory:
tools.py- Examples of various tool definitionsresources.py- Examples of resource handlingprompt.py- Examples of prompt creation
To run an example:
cd src/example
python tools.pyConfiguration
The MCP server can be configured with various options:
mcp = MCP()
mcp.init_app(
app,
name="my-awesome-server",
import_name=__name__,
url_prefix="/mcp", # Endpoint prefix for MCP routes
version="1.0.0"
)Development
Prerequisites
Python 3.9+
Flask 3+
Pydantic 2+
Setup
# Clone the repository
https://github.com/maocatooo/flask-mcp-plus
cd flask-mcp-plus
# Install dependencies
uv sync
License
This project is licensed under the Apache 2.0 License - see the LICENSE file for details.
Related Projects
Model Context Protocol - The official MCP specification
Flask - The web framework used
Pydantic - Data validation library
fastmcp - A high-performance MCP implementation
Support
If you encounter any issues or have questions, please file an issue on the GitHub repository.
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