sarvamai/sarvam-mcp

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Official Sarvam MCP server. Exposes every public Sarvam API — STT, TTS, Translate, Transliterate, Language ID, Text Analytics, LLM (30B / 105B), Vision Document Intelligence, Pronunciation...

概要

Official Sarvam MCP server. Exposes every public Sarvam API — STT, TTS, Translate, Transliterate, Language ID, Text Analytics, LLM (30B / 105B), Vision Document Intelligence, Pronunciation...

README

sarvam-mcp

Official Sarvam MCP server. Exposes every public Sarvam API — STT, TTS, Translate, Transliterate, Language ID, Text Analytics, LLM (30B / 105B), Vision Document Intelligence, Pronunciation Dictionaries — as first-class MCP tools so any MCP-aware client (Claude Desktop, Claude Code, Cursor, Windsurf, Zed) can call Sarvam with zero boilerplate.

Cross-platform Python package: macOS, Windows, and Linux (Python 3.11+).

Quickstart

1. Get your API key

2. Add to your MCP client

Paste this into your MCP config JSON:

{
  "mcpServers": {
    "sarvam": {
      "command": "uvx",
      "args": ["sarvam-mcp"],
      "env": {
        "SARVAM_API_KEY": "sk_..."
      }
    }
  }
}

Replace sk_... with your actual API key.

If you’ve installed via pip install sarvam-mcp, you can use the console script directly:

{
  "mcpServers": {
    "sarvam": {
      "command": "sarvam-mcp",
      "env": {
        "SARVAM_API_KEY": "sk_..."
      }
    }
  }
}

3. Config file locations

Client	Config path
Cursor	`~/.cursor/mcp.json` (macOS/Linux) · `%USERPROFILE%\.cursor\mcp.json` (Windows)
Claude Desktop	`~/Library/Application Support/Claude/claude_desktop_config.json` (macOS) · `%APPDATA%\Claude\claude_desktop_config.json` (Windows)
Claude Code	`claude mcp add sarvam -- uvx sarvam-mcp` (then set `SARVAM_API_KEY` env var)
Windsurf	Cascade settings → MCP servers
Zed	`settings.json` → `context_servers`

Alternative: credentials file

Instead of setting SARVAM_API_KEY in the JSON config, you can store it in ~/.sarvam/credentials:

api_key = sk_...

The server checks SARVAM_API_KEY env var first, then falls back to ~/.sarvam/credentials.

Install

# Option A: run directly (no install needed)
uvx sarvam-mcp

# Option B: install globally
pip install sarvam-mcp

Tools

All defaults below reflect the latest non-deprecated models.

Tool	What it does	Default model
`sarvam_stt_transcribe`	Audio file → transcript (5 modes)	`saaras:v3`
`sarvam_tts_speak`	Text → audio file	`bulbul:v3`
`sarvam_tts_stream`	Text → streamed audio	`bulbul:v3`
`sarvam_translate`	Cross-language text translate	`mayura:v1`
`sarvam_transliterate`	Script conversion	—
`sarvam_identify_language`	Language + script detect	—
`sarvam_text_analytics`	Typed Q&A over text	—
`sarvam_llm_complete`	Chat completions	`sarvam-105b`
`sarvam_vision_extract`	Document Intelligence	Sarvam Vision
`sarvam_vision_job_status`	Poll Document Intelligence job	—
`sarvam_pronunciation_list`	List pronunciation dictionaries	—
`sarvam_pronunciation_get`	Get a pronunciation dictionary	—
`sarvam_pronunciation_create`	Create a pronunciation dictionary	—
`sarvam_pronunciation_delete`	Delete a pronunciation dictionary	—

Configuration

Env var	Default	Description
`SARVAM_API_KEY`	—	Required. API key from dashboard.sarvam.ai.
`SARVAM_API_BASE_URL`	`https://api.sarvam.ai`	Override for testing/staging.
`SARVAM_MCP_BASE_PATH`	`~/Desktop`	Where audio/document files land.
`SARVAM_AUDIO_OUTPUT_MODE`	`files`	`files` \| `resources` \| `both`.

Two namespaces

The server exposes tools across two namespaces:

sarvam_tools_* — runtime tools. Call Sarvam APIs to do things (transcribe, speak, translate, etc.).
sarvam_code_* — builder tools. Help you write code that uses Sarvam: docs, endpoint shapes, language lists, code snippets, starter projects.

Development

uv venv && source .venv/bin/activate
uv pip install -e ".[dev]"
pytest -q
mcp dev src/sarvam_mcp/server.py

View this README on GitHub

インストール

uvx sarvam-mcp

設定

{
  "mcpServers": {
    "sarvam": {
      "command": "uvx",
      "args": ["sarvam-mcp"],
      "env": {
        "SARVAM_API_KEY": "sk_..."
      }
    }
  }
}