Assistant MCP Server
An MCP server that dynamically loads tools from an external JSON file configured via an environment variable.
Assistant MCP Server
Development
After cloning the repository, run the command to install the dependencies:
yarn install
You should also add the tools.json file to the root of the project, for example:
{
"tools": [
{
"name": "architecture_info",
"description": "Obtaining mandatory information about the architecture of frontend application projects",
"inputSchema": {},
"plugin": {
"name": "file",
"args": {
"path": "/path/to/folder/public/architecture.md"
}
}
},
{
"name": "search_tasks",
"description": "Before executing this function, you must retrieve the project architecture information from 'architecture_info'. This is mandatory information and you must respect it. After that you need to find the task you are talking about, analyze what needs to be done and implement it in the project according to the architecture and requirements. You don't need to invent anything additional from yourself, just what is required",
"inputSchema": {},
"plugin": {
"name": "file",
"args": {
"path": "/path/to/folder/public/tasks.txt"
}
}
},
{
"name": "optimize_prompt",
"description": "Generates a final, structured prompt for the AI model based on the provided context sections and instructions. This tool should be called after all relevant data has been collected. The result is intended to be used as the FINAL prompt for the AI. Clients must use the returned prompt as the input for the AI model.",
"inputSchema": {
"type": "object",
"properties": {
"sections": {
"type": "array",
"items": {
"type": "object",
"properties": {
"title": { "type": "string" },
"content": { "type": "string" }
},
"required": ["title", "content"]
}
},
"instructions": { "type": "string" }
},
"required": ["sections"]
},
"plugin": {
"name": "promptOptimizer",
"args": {}
}
}
]
}
To build the project, you must execute the command:
yarn build
Connecting to a local server
{
"mcpServers": {
"mcp-assistant-local": {
"command": "npx",
"args": [
"tsx",
"/path/to/folder/src/index.ts"
],
"env": {
"TOOLS_PATH": "/path/to/folder/tools.json"
}
}
}
}
License
This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
Похожие серверы
Scout Monitoring MCP
спонсорPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
спонсорAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
LMAD - Laravel MCP API Discovery
Laravel MCP server that exposes API routes, controllers, FormRequest validation rules, and response schemas to AI agents
WordPress MCP Server
Interact with WordPress sites via the REST API. Manage content, posts, and site configurations for multiple sites using natural language.
Ansible & OpenShift Automation
Provides tools to interact with the Ansible Automation Platform API for automation tasks.
MCP Servers Collection
A collection of MCP servers for Claude Desktop, providing access to network tools, code linters, and Proxmox virtualization management.
MasterGo Magic MCP
A standalone MCP service that connects MasterGo design tools with AI models, enabling them to retrieve DSL data directly from design files.
MCP Server with GitHub OAuth
A remote MCP server with built-in GitHub OAuth support, designed for deployment on Cloudflare Workers.
Playwright MCP
Generate Playwright tests with AI assistants by providing real-time access to the browser DOM, interactions, and screenshots.
Code Index MCP
A server for code indexing, searching, and analysis, enabling LLMs to interact with code repositories.
Code Reaper
CodeReaper is an AI-driven MCP tool for Cursor that finds and removes dead JavaScript by exploring real UIs and capturing V8 coverage
NeoCoder
Enables AI assistants to use a Neo4j knowledge graph for standardized coding workflows, acting as a dynamic instruction manual and project memory.