MCP Project Helper
A lightweight, extensible MCP server for running prompt-based tools and file utilities, with support for custom prompts.
mcp-project-helper
A lightweight, extensible MCP (Model Context Protocol) server for running prompt-based tools and file utilities. Designed for easy integration, testing, and extension with custom prompts.
Features
- Prompt-based tools: Easily add new tools by writing simple JSON prompt files.
- File utilities: Includes tools for reading, writing, moving, and deleting files and directories.
- Custom prompts: Place your own prompt definitions in the
custom_prompts/directory. - Multiple transports: Supports STDIO, SSE, and HTTP for flexible integration.
- Extensive tests: Includes a test script to verify all tool endpoints.
Getting Started
Build Locally
make build-local
⚡ Quick Start
Install via go install
To quickly install the latest version from the repository:
go install github.com/ad/mcp-project-helper@latest
The binary will appear in $GOBIN or $HOME/go/bin (make sure this path is in your $PATH).
1. Build from source
# Clone the repository
git clone https://github.com/ad/mcp-project-helper.git
cd mcp-project-helper
go mod tidy
# Local build
make build-local
# Or manually
go build -o mcp-project-helper main.go
# Local build
make build-local
# Or manually
go build -o mcp-project-helper main.go
# Docker build
make build
Run the Server
- STDIO (default):
./mcp-project-helper
- SSE:
./mcp-project-helper -transport sse -port 8080 - HTTP:
./mcp-project-helper -transport http -port 8080
Run Tests
./test.sh
🔌 Integration
VS Code
go install github.com/ad/mcp-project-helper@latest
Добавьте в settings.json:
{
"mcp": {
"servers": {
"helper": {
"type": "stdio",
"command": "/absolute/path/to/project-helper",
"args": ["-transport", "stdio"]
}
}
}
}
Docker (VS Code)
{
"mcp": {
"servers": {
"helper": {
"type": "stdio",
"command": "docker",
"args": [
"run", "--rm", "-i",
"danielapatin/mcp-project-helper:latest",
"-transport", "stdio"
]
}
}
}
}
Claude Desktop
{
"mcpServers": {
"helper": {
"command": "/absolute/path/to/mcp-project-helper",
"args": ["-transport", "stdio"]
}
}
}
Adding Custom Tools
- Create a JSON file in
custom_prompts/(seepalette.jsonfor an example). - Each tool must define a
descriptionand apromptfield. - The tool will be automatically registered and available via the MCP protocol.
Example Tools
- tool-generator: Generates a tool description and prompt template based on a user query.
- palette: Suggests a harmonious color palette for a given color.
Project Structure
main.go— Main server entry pointprompts/— Built-in prompt toolscustom_prompts/— User-defined prompt toolstest.sh— End-to-end test scriptMakefile— Build and run commands
License
MIT
相关服务器
Alpha Vantage MCP Server
赞助Access financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
MCP Jupyter Complete
A server for Jupyter notebook manipulation with position-based operations and VS Code integration.
MLflow Prompt Registry
Access prompt templates managed in an MLflow Prompt Registry. Requires a running MLflow server configured via the MLFLOW_TRACKING_URI environment variable.
Remote MCP Server on Cloudflare
Deploy a remote MCP server without authentication on Cloudflare Workers.
Godot MCP
A plugin for modular communication between external processes and the Godot game engine.
Swagger MCP
Scrapes Swagger UI to dynamically generate MCP tools at runtime using LLMs.
The Game Crafter MCP Server
Indie board game designers, tabletop creators, and TGC users who want to manage their projects through an AI assistant instead of navigating the TGC web interface manually.
refactor-mcp
Refactor code using regex-based search and replace.
Terraform Registry MCP Server
An MCP server for interacting with the Terraform Registry API. It allows querying for providers, resources, modules, and supports Terraform Cloud operations.
Claude Code Memory Server
A Neo4j-based MCP server providing persistent memory and contextual assistance for Claude Code.
Deliberate Reasoning Engine (DRE)
Transforms linear AI reasoning into structured, auditable thought graphs, enabling language models to externalize their reasoning process as a directed acyclic graph (DAG).