TransBench
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| PUBMED_API_KEY | No | Optional API key for higher NCBI/PubMed rate limits | |
| LLM_TEMPERATURE | No | Forces deterministic LLM clients; set to 0 | 0 |
| TRANSBENCH_MODE | No | Optional toggle: 'live' (default), 'golden', or 'snapshot' | |
| ANTHROPIC_API_KEY | Yes | Required API key for the engine's own Anthropic calls | |
| PYTHONDONTWRITEBYTECODE | No | Prevents Python from writing .pyc/__pycache__ during imports | 1 |
| TRANSBENCH_GOLDEN_BRIEF | No | Path to the golden brief file for golden mode | snapshots/flagship_golden_brief.json |
| TRANSBENCH_RETRIEVAL_SNAPSHOT | No | Path to the retrieval snapshot file for snapshot mode | snapshots/flagship_retrieval_snapshot.json |
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": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_experimentA | Generate a grounded translational research brief from ANY clinical or biomedical observation — a disease's drug response/resistance, a drug's adverse effect/toxicity, or any mechanism (not limited to any one domain). ASYNC (submit + poll): the full pipeline (decompose -> hypothesize ->
retrieve -> grade -> entail -> novelty-check -> design -> assemble) runs
~60-120s, longer on a cold first call — longer than an MCP client will wait
on one call. So this tool does NOT block: it STARTS the run and returns
immediately with a job handle. You MUST then poll
Args: observation: A free-text clinical/biomedical observation (3-8000 characters) — any disease, drug response/resistance, adverse effect, or mechanism. Examples: "58F, resistant hypertension despite ACEi + CCB + thiazide; elevated hs-CRP" or "30M on amiodarone for AF, developed neutropenia". focus_drug: Optional drug name to focus the analysis on. Omit ("") to let the pipeline infer relevant drugs from the observation itself. Returns:
Immediately: |
| search_grounded_evidenceA | Look up PubMed-grounded mechanistic evidence for ANY clinical,
pharmacological, or mechanistic question (utility / fallback tool — a
lighter-weight sibling of ASYNC (submit + poll): runs the SAME full TransBench pipeline as
Args: question: A free-text clinical/pharmacological/mechanistic question (3-8000 characters), any domain. Returns:
Immediately: |
| get_experiment_resultA | Poll for the result of a run started by Args:
job_id: The Returns:
- still working: |
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
Each tool has a distinct, non-overlapping purpose: generate_experiment starts a job for a research brief, search_grounded_evidence starts a job for evidence retrieval, and get_experiment_result polls for results. Descriptions are detailed and clearly differentiate them.
All tool names follow a consistent verb_noun pattern using snake_case (generate_experiment, get_experiment_result, search_grounded_evidence). There is no mixing of conventions or ambiguous verbs.
With 3 tools, the set is small but well-scoped for an async job submission and polling pattern. It covers the essential operations without being overly minimal, though a tool to list or cancel jobs might be missing.
The tools cover the core workflow: submitting two types of jobs and retrieving results. There are no obvious gaps for the stated purpose, but additional features like job cancellation or listing completed jobs would enhance completeness.