What is Sarvam Mcp

Sarvam-MCP is a minimal Model Context Protocol (MCP) server that provides access to a variety of Sarvam AI language and speech tools as callable functions, facilitating easy integration and experimentation with Sarvam’s capabilities.

Use cases

Use cases for Sarvam-MCP include transcribing audio for meetings, generating voiceovers for videos, translating customer inquiries in real-time, and retrieving documentation for quick reference during development.

How to use

To use Sarvam-MCP, you need to set up your personal Sarvam API key in a .env file or a client-specific mcp.json. Once configured, you can call various tools such as Speech to Text, Text to Speech, and others through the MCP interface.

Key features

Key features of Sarvam-MCP include Speech to Text, Text to Speech, Speech to Text Translate, Call Analytics, Text Translation, and a Documentation Retriever for accessing relevant Sarvam AI documentation.

Where to use

Sarvam-MCP can be used in various fields such as customer service for call analytics, content creation for text-to-speech applications, and language translation services across different industries.

MCP Server for Sarvam AI Tools

This project provides a minimal Model Context Protocol (MCP) server that exposes a set of Sarvam AI language and speech tools as callable functions. The server is designed for easy integration and experimentation with Sarvam’s capabilities via the MCP interface.

Offered Tools

• Speech to Text: Transcribe audio files to text using Sarvam’s ASR models.
• Text to Speech: Convert text into natural-sounding speech in various languages and voices.
• Speech to Text Translate: Transcribe and translate audio directly to a target language.
• Call Analytics: Analyze call audio for summaries, insights, and question answering.
• Text Translation: Translate text between supported languages using Sarvam’s translation models.
• Sarvam Documentation Retriever (get_sarvam_documentation_file): Retrieves the content of the most relevant local Sarvam AI markdown documentation file.
  • Searches in docs/api-ref, docs/cookbook, and docs/docs-section by default.
  • Parameters:
    • search_term (string, required): Keywords, topic description, or filename to search for.
    • doc_area (string, optional): Specific documentation area (e.g., ‘api-ref’, ‘cookbook’) to narrow the search.

All tools are implemented using the official Sarvam SDK and are discoverable via the MCP server interface.

Configuration

To use the tools that interact with the Sarvam AI API, you need to provide your personal Sarvam API key.

Method 1: Using a .env file (Recommended for direct use)

1. In the root directory of this server, create a file named .env.
2. Add your Sarvam API key to this file in the following format:

   SARVAM_API_KEY=your_actual_sarvam_api_key_here
   

3. Replace your_actual_sarvam_api_key_here with your key.
4. The server will automatically load this key when it starts.

Method 2: Using Client-Specific mcp.json (for MCP Clients like Cursor, Claude Desktop)

If you are integrating this server with an MCP client application that uses an mcp.json configuration file (or similar), you can usually set the API key as an environment variable within that client’s configuration for this server.

For example, in the client’s mcp.json file, the entry for this server might look like:

Replace YOUR_SARVAM_API_KEY_HERE with your actual key and adjust the command and args to point to where you have this MCP server and how you want to run it.

Note: Environment variables set through the client’s mcp.json will typically override those in a local .env file if both are present.

Ensure your .env file is included in your .gitignore if you are managing this project with Git.