MCP Servers

This repository contains two MCP (Model Context Protocol) servers:

1. File Finder MCP - for searching files

2. Whisper STT MCP - for converting speech to text

File Finder MCP Server

This is a Model Context Protocol (MCP) server that provides file search functionality. It allows you to search for files that contain a specified text fragment in their names.

Prerequisites

• Node.js (version 14 or higher)

• npm (version 6 or higher)

• Python 3.6 or higher (for HTTP server)

Installation

1. Clone or download this repository

2. Go to the project directory

3. Install dependencies:

   npm install

4. Assemble the project:

   npm run build

Starting the server

The project provides several options for launching the MCP server:

Option 1: Direct launch of MCP server

You can run the MCP server directly using Node.js:

npm start

or

node build/index.js

This will start the server and it will listen for JSON-RPC requests on stdin/stdout.

Option 2: Launch HTTP server and MCP proxy

This option uses a Python HTTP server and an MCP proxy that forwards requests to the HTTP server:

1. First, start the HTTP server:

   npm run start:python

   or

   python main.py

2. Then in another terminal, run MCP proxy:

   npm run start:http

   or

   node build/index-http.js

Option 3: Integration with VS Code (Cline extension)

To integrate the server with VS Code and the Cline extension:

1. Find the MCP settings file:

   • Windows: %APPDATA%\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json

   • macOS: ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json

   • Linux: ~/.config/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json

2. Add the following configuration to the mcpServers object in the settings file:

"file-finder-mcp": {
  "command": "node",
  "args": ["<ПОЛНЫЙ_ПУТЬ_К_ПРОЕКТУ>/build/index.js"],
  "disabled": false,
  "autoApprove": []
}

To use HTTP proxy:

"file-finder-mcp-http": {
  "command": "node",
  "args": ["<ПОЛНЫЙ_ПУТЬ_К_ПРОЕКТУ>/build/index-http.js"],
  "disabled": false,
  "autoApprove": []
}

Replace <ПОЛНЫЙ_ПУТЬ_К_ПРОЕКТУ> with the actual path to your project directory.

3. Restart VS Code to load the updated settings.

Available tools

MCP server provides one tool:

• search_files : Searches for files that contain the specified fragment in their names

  • Parameters:

    • fragment (string, required): Text fragment to search for in file names

Example of use

<use_mcp_tool>
<server_name>file-finder-mcp</server_name>
<tool_name>search_files</tool_name>
<arguments>
{
  "fragment": ".py"
}
</arguments>
</use_mcp_tool>

This example finds all files that contain ".py" in their names.

HTTP server (main.py)

In the root directory of the project there is a file main.py , which implements an HTTP server for searching files. This server provides a REST API for searching files that contain a specified fragment in their names.

Starting HTTP server

1. Go to the root directory of the project

2. Start the server using Python:

   python main.py

3. The server will be launched at http://localhost:8080

Using the API

To search for files, send a GET request to /search with the q query parameter:

http://localhost:8080/search?q=.json

This query will return a JSON array with information about all files that contain ".json" in their names. Each element of the array contains the following fields:

• name : file name

• path : absolute path to the file

• size : file size in bytes

• created : date and time of file creation

Example answer:

[
    {
        "name": "package.json",
        "path": "/absolute/path/to/package.json",
        "size": 1234,
        "created": "Wed Feb 26 17:00:00 2025"
    }
]

Related MCP server: Everything Search MCP Server

Whisper STT MCP Server

This is a Model Context Protocol (MCP) server that provides speech-to-text functionality using the faster-whisper library. It allows transcribing audio data into text with automatic language detection.

Prerequisites

• Node.js (version 14 or higher)

• npm (version 6 or higher)

• Python 3.6 or higher

• faster-whisper (install with pip install faster-whisper )

Installation

1. Clone or download this repository

2. Go to the project directory

3. Install dependencies:

   npm install
   pip install faster-whisper

4. Assemble the project:

   npm run build

Starting the server

The project provides several options for running the Whisper MCP server:

Option 1: Direct launch of MCP server

You can run the MCP server directly using Node.js:

npm run start:whisper

or

node build/whisper-index.js

This will start the server and it will listen for JSON-RPC requests on stdin/stdout.

Option 2: Launch HTTP server and MCP proxy

This option uses a Python HTTP server and an MCP proxy that forwards requests to the HTTP server:

1. First, start the HTTP server:

   npm run start:whisper:python

   or

   python whisper_server.py

2. Then in another terminal, run MCP proxy:

   npm run start:whisper:http

   or

   node build/whisper-index-http.js

Option 3: Integration with VS Code (Cline extension)

To integrate the server with VS Code and the Cline extension:

1. Find the MCP settings file:

   • Windows: %APPDATA%\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json

   • macOS: ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings\cline_mcp_settings.json

   • Linux: ~/.config/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json

2. Add the following configuration to the mcpServers object in the settings file:

"whisper-stt-mcp": {
  "command": "node",
  "args": ["<ПОЛНЫЙ_ПУТЬ_К_ПРОЕКТУ>/build/whisper-index.js"],
  "disabled": false,
  "autoApprove": []
}

To use HTTP proxy:

"whisper-stt-mcp-http": {
  "command": "node",
  "args": ["<ПОЛНЫЙ_ПУТЬ_К_ПРОЕКТУ>/build/whisper-index-http.js"],
  "disabled": false,
  "autoApprove": []
}

Replace <ПОЛНЫЙ_ПУТЬ_К_ПРОЕКТУ> with the actual path to your project directory.

3. Restart VS Code to load the updated settings.

Available tools

MCP server provides one tool:

• transcribe_audio : Transcribes audio data to text using faster-whisper

  • Parameters:

    • audio_base64 (string, required): Audio data in base64 format

    • language (string, optional): Language code (e.g. "en", "ru"). If not specified, the language will be detected automatically.

Example of use

<use_mcp_tool>
<server_name>whisper-stt-mcp</server_name>
<tool_name>transcribe_audio</tool_name>
<arguments>
{
  "audio_base64": "BASE64_ENCODED_AUDIO_DATA",
  "language": "ru"
}
</arguments>
</use_mcp_tool>

This example converts audio data to text, assuming the audio is in Russian.

HTTP server (whisper_server.py)

In the root directory of the project there is a file whisper_server.py , which implements an HTTP server for converting speech to text. This server provides a REST API for transcribing audio data into text.

Starting HTTP server

1. Go to the root directory of the project

2. Start the server using Python:

   python whisper_server.py

3. The server will be launched at http://localhost:8081

Using the API

To transcribe audio, send a POST request to /transcribe with a JSON body containing:

• audio : a base64 encoded string containing audio data

• language (optional): language code (e.g. "en", "ru")

Example request:

{
  "audio": "BASE64_ENCODED_AUDIO_DATA",
  "language": "ru"
}

The answer will contain:

• text : full transcribed text

• segments : array of segments with timestamps

• language : a specific language

• language_probability : probability of detecting a language

Example answer:

{
  "text": "Это пример транскрибированного текста.",
  "segments": [
    {
      "start": 0.0,
      "end": 2.5,
      "text": "Это пример"
    },
    {
      "start": 2.5,
      "end": 4.0,
      "text": "транскрибированного текста."
    }
  ],
  "language": "ru",
  "language_probability": 0.98
}

Troubleshooting

• If you get the "No connection found for server" error, make sure you restart VS Code after updating your MCP settings.

• If the server does not respond, check that the path in the MCP settings is correct and points to the compiled JavaScript file.

• Make sure the server is built correctly by running npm run build before attempting to use it.

• To use an HTTP proxy, make sure that the appropriate HTTP server is running (on port 8080 for file-finder or 8081 for whisper-stt).

• If you have problems with faster-whisper, make sure the library is installed correctly and you have the necessary dependencies to work with GPU (if you are using GPU).

Project structure

Below is a list of the main project files and their purposes:

Root directory

• src/index.ts - TypeScript MCP file search server source code (direct implementation)

• src/index-http.ts - Source code for TypeScript MCP proxy for HTTP file search server

• src/whisper-index.ts - Source code for TypeScript MCP speech-to-text server (direct implementation)

• src/whisper-index-http.ts - Source code for TypeScript MCP proxy for HTTP speech-to-text server

• build/index.js - Compiled JavaScript code of MCP server for searching files

• build/index-http.js - Compiled JavaScript code of MCP proxy for searching files

• build/whisper-index.js - Compiled JavaScript code of MCP server for converting speech to text

• build/whisper-index-http.js - Compiled JavaScript code of MCP proxy for converting speech to text

• tsconfig.json - TypeScript configuration

• package.json - Description of the package and dependencies

• main.py - Python HTTP server for file retrieval

• whisper_server.py - Python HTTP server for speech to text conversion

• README.md - Project documentation (this file)