Sarvam

sarvam-mcp/  v0.1   ──────────────────────────────────────────────────

A focused, type-safe MCP server for the Sarvam AI API. Lets Claude Code (or any MCP-compatible client) speak to Sarvam's models — chat, translation, transliteration, language detection, speech-to-text, and text-to-speech — across 10 Indic languages plus English.

[!IMPORTANT] This project is not affiliated with, endorsed by, or associated with Sarvam AI. It's an unofficial MCP wrapper that calls the public Sarvam API using your own API key. No keys, audio, or text are routed through any third-party server.

[!NOTE] Requires a Sarvam AI API key. Get one at dashboard.sarvam.ai. Free tier is generous enough to test all six tools.

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What it does

Wraps Sarvam's public REST surface in a small set of well-defined MCP tools. Tools are typed end-to-end with Zod schemas, validated at the boundary, and surface useful error messages when something goes wrong.

                  ┌───────────────┐
                  │ Claude Code   │
                  │ (or any MCP   │
                  │  client)      │
                  └───────┬───────┘
                          │ stdio (MCP)
                          ▼
                  ┌───────────────┐
                  │  sarvam-mcp   │
                  └───────┬───────┘
                          │ HTTPS · api.sarvam.ai
                          ▼
                  ┌───────────────┐
                  │  Sarvam API   │
                  │  (Sarvam-105B │
                  │   · Mayura    │
                  │   · Saarika   │
                  │   · Bulbul)   │
                  └───────────────┘

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Why another wrapper?

Sarvam ships a great official SDK for Python and Node. This is the MCP-shaped surface that lets agentic clients call it directly — no SDK code, no glue layer.

• 6 tools, deliberately scoped. Every tool is documented, typed, and tested.
• Strict TypeScript. No any, no implicit returns, noUncheckedIndexedAccess on.
• Zod-validated boundaries. Every input is parsed before the network call.
• Typed errors. SarvamApiError, SarvamRateLimitError, SarvamConfigError, SarvamValidationError — never bare Error.
• sarvam-mcp doctor. A diagnostic command that tells you exactly what's wrong with your setup.

Use this if you want a small, predictable surface you can read in an afternoon.

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The 6 tools

Tool	What it does	Sarvam endpoint
sarvam_chat	Chat completions (Sarvam-30B / Sarvam-105B), JSON mode supported	POST /v1/chat/completions
sarvam_translate	Bidirectional EN ↔ Indic and Indic ↔ Indic translation	POST /translate
sarvam_transliterate	Script conversion (Roman ↔ Devanagari, etc.)	POST /transliterate
sarvam_detect_language	Identify language and script of input text	POST /text-lid
sarvam_speech_to_text	Saarika v2.5 / Saaras v3 transcription from local audio file	POST /speech-to-text
sarvam_text_to_speech	Bulbul v3 synthesis. Returns base64 audio + optional WAV file	POST /text-to-speech

Document Intelligence (Sarvam Vision) is on the v0.2 roadmap — it's an async batch flow that deserves its own treatment.

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Install

Requires Node.js 20+.

npm install -g sarvam-mcp
# or, in a project:
npm install sarvam-mcp

For development:

git clone https://github.com/harshil1502/sarvam-mcp.git
cd sarvam-mcp
npm install
npm run build

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Setup — three steps

1. Get a Sarvam API key

dashboard.sarvam.ai → create key. Free tier is enough to test all six tools.

2. Export it

export SARVAM_API_KEY=<your_key>

(Or put it in a .env file and source it before launching the MCP client — see .env.example.)

3. Verify

sarvam-mcp doctor

You should see something like:

sarvam-mcp · doctor
─────────────────────────────────────────────
[ ok ] SARVAM_API_KEY env var
       Set (40 chars).
[ ok ] Language ID endpoint
       Detected: hi-IN (expected hi-IN).
[ ok ] Chat completions
       Got: ok
─────────────────────────────────────────────
all green — sarvam-mcp is ready.

If something fails, the doctor prints the exact reason.

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Use with Claude Code

Add to your ~/.claude.json MCP servers:

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

Then in Claude:

> translate "I'll be there at 9pm" to Tamil

[claude calls sarvam_translate]
→ "நான் இரவு 9 மணிக்கு அங்கு வருவேன்"

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Examples

Chat in Hindi

// tool call: sarvam_chat
{
  "messages": [
    { "role": "system", "content": "You are a helpful assistant. Reply in Hindi." },
    { "role": "user", "content": "What's the difference between Marathi and Hindi?" }
  ],
  "model": "sarvam-105b",
  "temperature": 0.4
}

Translate code-mixed text

// tool call: sarvam_translate
{
  "input": "मेरा नाम Harshil है and I work in AI",
  "source_language_code": "auto",
  "target_language_code": "en-IN",
  "mode": "code-mixed"
}
// → { "translated_text": "My name is Harshil and I work in AI" }

Transliterate a Hindi name to Roman script

// tool call: sarvam_transliterate
{
  "input": "हर्षिल पटेल",
  "source_language_code": "hi-IN",
  "target_language_code": "en-IN"
}
// → { "transliterated_text": "Harshil Patel" }

Identify language

// tool call: sarvam_detect_language
{ "input": "வணக்கம் உலகம்" }
// → { "language_code": "ta-IN", "script_code": "Taml" }

Transcribe a voice memo

// tool call: sarvam_speech_to_text
{
  "audio_path": "/Users/me/Downloads/voice-memo.m4a",
  "language_code": "hi-IN",
  "model": "saaras:v3",
  "with_diarization": true
}

Generate Tamil speech and save it

// tool call: sarvam_text_to_speech
{
  "inputs": ["நான் உங்களுக்கு உதவ முடியும்."],
  "target_language_code": "ta-IN",
  "speaker": "anushka",
  "output_path": "/tmp/reply.wav"
}
// → audio also written to /tmp/reply.wav

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Architecture

Four files, four responsibilities:

src/
├── client/sarvam.ts    ← single fetch wrapper, both auth schemes
├── tools/
│   ├── chat.ts         ← sarvam_chat
│   ├── translate.ts    ← translate · transliterate · detect_language
│   └── speech.ts       ← speech_to_text · text_to_speech
├── server.ts           ← MCP transport + tool registration
├── cli/doctor.ts       ← setup diagnostics
└── index.ts            ← entry point + argv routing

When the next Sarvam API release breaks something, drift is contained to one file.

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Strict TypeScript across the agent boundary

// tsconfig.json (excerpts)
{
  "strict": true,
  "noImplicitAny": true,
  "noUncheckedIndexedAccess": true,
  "noUnusedLocals": true,
  "noUnusedParameters": true,
  "noImplicitReturns": true
}

Agents will happily call your tool with null and then narrate the resulting error. Don't let them.

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Errors

Class	When it fires
SarvamConfigError	Missing SARVAM_API_KEY, unreadable audio file.
SarvamApiError	Any 4xx/5xx from Sarvam (other than 429). Includes status, endpoint, and body excerpt.
SarvamRateLimitError	429. Includes retryAfterSeconds if Sarvam sets Retry-After.
SarvamValidationError	Zod validation failed — the LLM passed bad arguments.

Retries are intentionally not auto-implemented. The LLM gets the error and decides what to do.

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Contributing / roadmap

v0.2 — Document Intelligence (Sarvam Vision):

• sarvam_doc_extract_start — kick off async OCR job
• sarvam_doc_extract_status — poll
• sarvam_doc_extract_results — fetch structured output

v0.3 — streaming (WebSocket TTS / STT) for low-latency voice agents.

PRs welcome. Run npm run typecheck && npm test before opening one.

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License

MIT © 2026 Harshil Patel