Assistant MCP Server

1

Add it to Claude Code

Run this in a terminal.

Run in terminal
claude mcp add -e "TOOLS_PATH=${TOOLS_PATH}" mcp-assistant -- npx tsx /path/to/folder/src/index.ts
Required:TOOLS_PATH
README.md

Define custom tools via config and generate optimized AI prompts.

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.

Tools (3)

architecture_infoObtaining mandatory information about the architecture of frontend application projects
search_tasksFinds and analyzes project tasks based on architecture requirements
optimize_promptGenerates a final, structured prompt for the AI model based on provided context and instructions

Environment Variables

TOOLS_PATHrequiredThe absolute path to the tools.json configuration file

Configuration

claude_desktop_config.json
{"mcpServers": {"mcp-assistant-local": {"command": "npx", "args": ["tsx", "/path/to/folder/src/index.ts"], "env": {"TOOLS_PATH": "/path/to/folder/tools.json"}}}}

Try it

Retrieve the project architecture information to understand the frontend structure.
Find the current tasks in the project and analyze what needs to be implemented.
Optimize this prompt for me: [insert context sections] with instructions to follow the project architecture.
Based on the architecture info, what are the next steps for the current task?

Frequently Asked Questions

What are the key features of Assistant MCP Server?

Define custom tools via a JSON configuration file. Retrieve project-specific architecture documentation. Automated task analysis based on project files. Structured AI prompt optimization and generation.

What can I use Assistant MCP Server for?

Standardizing AI responses by enforcing project architecture constraints. Managing and tracking development tasks directly through AI interactions. Creating consistent, high-quality prompts for complex coding tasks. Integrating local project documentation into the AI context window.

How do I install Assistant MCP Server?

Install Assistant MCP Server by running: yarn install && yarn build

What MCP clients work with Assistant MCP Server?

Assistant MCP Server works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Turn this server into reusable context

Keep Assistant MCP Server docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

Need the old visual installer? Open Conare IDE.
Open Conare