basic-mcp
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., "@basic-mcpcount words in 'Hello, world!'"
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.
Text Assistant MCP Server
A minimal MCP (Model Context Protocol) compatible server that provides simple tools, resources, and prompt templates for text processing. Built with FastAPI and FastMCP for seamless integration.
Features
š¹ Resources
/resources/example-textDescription: A sample paragraph of text that agents can read.
Content: "The quick brown fox jumps over the lazy dog. This sentence contains every letter of the alphabet."
File:
resources/example-text.txt
š¹ Tools
count_words(text: str) -> intDescription: Returns the number of words in the given text.
Input:
{"text": "your text here"}
to_uppercase(text: str) -> strDescription: Converts the input text to uppercase.
Input:
{"text": "your text here"}
š¹ Prompts
summarize_prompt(language: str, text: str)Template: "Summarize the following text in {language}:\n\n{text}"
Description: Allows the agent to generate a summary in the desired language by filling in
languageandtext.File:
prompts/summarize_prompt.txt
Related MCP server: mhlabs-mcp-tools
Behavior
The MCP server does not maintain memory.
The agent is responsible for discovering and choosing tools, reading resources, and filling in prompts.
If a tool uses an LLM internally (e.g. in future expansions), the MCP server would pay for that usage.
Installation & Setup
Prerequisites
Docker and Docker Compose
Docker Deployment
Build and run with Docker Compose:
docker-compose up --buildFor debugging with VS Code:
# Set DEBUG=true in .env file docker-compose up --build # Then attach debugger in VS Code
Usage
FastAPI Endpoints
GET /health- Health check endpointGET /mcp/tools- List available MCP toolsPOST /mcp/tools/{tool_name}- Execute MCP toolsGET /mcp/resources- List available MCP resourcesGET /mcp/resources/{resource_name}- Read MCP resourcesGET /mcp/prompts- List available MCP prompts
MCP Protocol
The server implements the Model Context Protocol using FastMCP and can be used with MCP-compatible clients.
Example MCP Client Configuration
{
"mcpServers": {
"text-assistant": {
"command": "docker",
"args": ["run", "--rm", "my-fastapi-app:1.0.0"],
"env": {}
}
}
}Development
Project Structure
basic-mcp/
āāā app.py # FastAPI application with FastMCP integration
āāā requirements.txt # Python dependencies
āāā Dockerfile # Docker container definition
āāā docker-compose.yml # Docker Compose configuration
āāā entrypoint.sh # Container startup script
āāā resources/ # Static resources
ā āāā example-text.txt
āāā prompts/ # Prompt templates
ā āāā summarize_prompt.txt
āāā .vscode/ # VS Code configuration
ā āāā launch.json # Debug configuration
āāā README.md # This fileDebugging
Set
DEBUG=truein your.envfileStart the container:
docker-compose up --buildIn VS Code, use "Attach to Docker Container" configuration
Set breakpoints and debug the FastAPI application
Adding New Features
Tools: Add new functions with
@mcp.tool("tool_name")decoratorResources: Add new files to the
resources/directoryPrompts: Add new template files to the
prompts/directory
License
This project is open source and available under the MIT License.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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- AlicenseAqualityCmaintenanceA minimal TypeScript MCP starter server that counts words and characters, ready to extend with custom tools.1MIT
- Flicense-qualityDmaintenanceA simple MCP server that provides basic utility tools for text manipulation, file operations, and calculations, intended to be connected to Claude AI desktop app.
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MCP server for AI dialogue using various LLM models via AceDataCloud
MCP server providing access to the Scorecard API to evaluate and optimize LLM systems.
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