This release is a pre-release and may not be stable for production use.
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:v4 |
sarvam_tts_speak |
Text → audio file | bulbul:v3, bulbul:v4-flash |
sarvam_tts_stream |
Text → streamed audio | bulbul:v3, bulbul:v4-flash |
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
1 maintainer
Metadata
1 maintainer
Release files for sarvam-mcp 0.2.11a2
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| sarvam_mcp-0.2.11a2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 178.8 kB
Release files / sarvam_mcp-0.2.11a2.tar.gz
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