Sarvam Mcp

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

Sign up or log in at dashboard.sarvam.ai/key-management and copy your API key (sk_...).

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-30b | | 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

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: sarvamai
• Source: sarvamai/sarvam-mcp
• License: MIT
• Homepage: https://mcp.sarvam.ai

Install and usage instructions live in the source repository linked above.