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mcpcreatioserver

mcpcreatioserver

Local
github.com/mpawlikcreatioDeveloper Tools1Updated 62w ago

About mcpcreatioserver

mcpcreatioserver is a local Node.js MCP server for Creatio development, letting LLM tools such as Copilot Agents read guide and prompt files alongside an IDE. It provides file listing and reading tools, with support for adding custom tools.

Key features

  1. 01List guide text files
  2. 02List prompt files
  3. 03Read local files
  4. 04Add custom tools

Use cases

  1. 01Let Copilot Agents consult Creatio guides
  2. 02Load custom prompts as needed
  3. 03Provide file content in a local IDE workflow

MCP support

The server exposes three tools to MCP clients: listing guide files, listing prompt files, and reading local files. It communicates over stdio and can be tested in a browser with Inspector.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"mcpCreatioServer": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/inspector"
]
}
}
}
Run commandnpx -y @modelcontextprotocol/inspector

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@modelcontextprotocol/inspector

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Project Description

This project is a Node.js application for Windows OS called MCP Server. It serves as a local middleware for seamless communication between LLM-based tools (e.g., Copilot Agents). The server is designed to be run locally, ideally alongside an IDE like Visual Studio Code or Visual Studio.

MCP Server uses the third-party library @modelcontextprotocol/sdk, which allows you to run and test it in a web browser using the Inspector tool.

The project includes a predefined ./data directory that contains documentation and guide files used to assist with coding in the Creatio environment. Additionally, a ./data/prompts subfolder contains prompt files used by Copilot Agents to guide their behavior and output.

Configuration

Set the following environment variables:

  • GUIDE_FILES_DIR: Path to the directory containing your local guide files (e.g., .\\data).
  • PROMPT_DIR: Path to your prompt directory (e.g., .\\dat\\prompts). Prompt files must be .txt files and start with the prefix prompt_.

You can set these variables in a .env file or pass them directly in the terminal when running the app. Keep in mind having dobule "\" in your path names.

Example .env file:

GUIDE_FILES_DIR=C:\\pathToYourProject\\mcpLocalServer\\data\
PROMPT_DIR=C:\\pathToYourProject\\mcpLocalServer\\data\\prompts

💡 The paths should directly point to the folders where your guide and prompt files are located. It’s recommended to create a prompts subfolder under data.

Features

There are 3 build-in tools which you can use:

  • ListAvailableFilesTool – Lists all .txt files located in the data directory.
  • ListPromptsTool – Lists all prompt files located in the data/prompts directory.
  • ReadLocalFileTool – Reads and returns the content of a file from either data or data/prompts, depending on the file prefix.

Usage

  1. Install dependencies:

    npm install
    
  2. Configure environment variables using a .env file or directly in the terminal.

  3. Build the project:

    npm run build
    
  4. Run the server for browser testing:

    npx @modelcontextprotocol/inspector build/index.js
    
  5. Use the MCP-compatible client (like Copilot for Visual Studio Code) to interact with the server.

Usage with Visual Studio Code

To integrate with Copilot:

  1. Create a .vscode directory in your project.
  2. Add a mcp.json file with the following content:
{
  "inputs": [],
  "servers": {
    "local": {
      "command": "node",
      "args": ["C:\\pathToMcpLocalServerProjectInYourPC\\build\\index.js"]
    }
  }
}
  1. Follow the instructions from the official documentation to enable MCP support in VS Code.

  2. Start your server if is disabled with a command: ctrl+shift+p MCP:List Servers -> next chose you server Name and click action [""Start","Stop","Restart"]

  3. You should see MCP server Logs in OUTPUT terminal: 2025-05-30 08:35:10.855 [warning] [server stderr] ✅ Local MCP server running on stdio 2025-05-30 08:35:10.864 [info] Discovered 3 tools

⚠️ Make sure you're using the latest or pre-release version of Visual Studio Code that supports Agents.

Example prompt using guide files and custom prompts: You can find more examples in "../docs/VisualCode_Copilot_Examples"


Description: 💾 Create C# Class (Creatio Style)
Prompt text:
Use the local MCP server.

Step 1: Load the prompt file named "prompt_csharp_class_authoring.txt" using the "read_local_file" tool with the argument "fileName".

Step 2: Once the file is loaded, execute all instructions defined in that file. If those instructions require using additional tools, follow them accordingly.

Step 3: After completing all steps from the prompt file, generate a C# (.cs) file with a class named House. The class should contain Windows and Doors properties, and include methods to build them.

Ensure that the implementation follows all guidelines and conventions from the loaded prompt file.

Customization

You can extend this project by adding your own guide or prompt files:

  • Add a guide file: Create a .txt file with the prefix guide_ and place it in the folder defined by GUIDE_FILES_DIR.
  • Add a prompt file: Create a .txt file with the prefix prompt_ and place it in the folder defined by PROMPT_DIR.

You can also develop custom tools:

  1. Create a new YourTool.ts file in the src/tools directory.
  2. Register the tool in localMcpServer.ts.
  3. Rebuild the project before running tests.

License

This project is licensed under the MIT License.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.