dualtran-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| DUALTRAN_MODEL | No | Model name for the AI provider, e.g. gpt-4o-mini. | |
| DUALTRAN_ENGINE | No | Default engine: google | ai. Defaults to google. | |
| DUALTRAN_API_KEY | No | API key for the chosen AI provider (optional; only needed for the AI engine). | |
| DUALTRAN_BASE_URL | No | Optional endpoint override for the AI provider. | |
| DUALTRAN_PROVIDER | No | AI provider to use for the optional AI engine, e.g. openai | anthropic | google | deepseek | mistral | groq | xai | … Google translation works out of the box without this. | |
| DUALTRAN_TARGET_LANG | No | Default target language, e.g. en. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| translate_textB | Translate one piece of text with Google or the configured AI provider (BYOK). |
| translate_batchA | Translate up to 50 texts in one call (one batched Google request, or one AI call per text). |
| list_enginesA | Report which translation engines are available and how the AI engine is configured (never the key itself). |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
The three tools have clearly distinct purposes: single-text translation, batched translation, and engine introspection. An agent can easily select the right one with no overlap.
All names follow a consistent snake_case verb_noun pattern (translate_text, translate_batch, list_engines). The convention is predictable and readable.
Three tools is at the low end but reasonable for a narrow translation-focused server. Each tool earns its place, though the surface is slightly thin.
Core translation workflows (single, batch) plus engine introspection are covered. Minor gaps like explicit per-call engine selection or language detection could be worked around.