Tamarind Bio

Tamarind Bio

Tamarind Bio is a cloud platform that runs computational biology tools — structure prediction, protein and antibody design, docking, binding-affinity, MSA generation, and molecular dynamics — on managed GPUs. Users submit sequences or structures and get back predicted structures, designs, and biophysical scores, without provisioning their own hardware. It exposes hundreds of tools (AlphaFold, Boltz-2, Chai-1, RFdiffusion, ProteinMPNN, BoltzGen, ESMFold2, DiffDock, Autodock Vina, and many more) through one uniform job API.

Official docs: app.tamarind.bio/api-docs · platform UI at app.tamarind.bio

Canonical sources — fetch these, don't rely on a stale copy

Tamarind publishes live, machine-readable sources. Prefer fetching them at runtime over trusting any hardcoded list — tool names, schemas, and endpoints change frequently:

• https://app.tamarind.bio/llms.txt — LLM index: links to the spec, API docs, and MCP guide.
• https://app.tamarind.bio/openapi.yaml — OpenAPI 3.0 spec for the 8 core job endpoints (submit-job/-batch, jobs, result, upload, files, delete-job/-file; auth ApiKeyAuth). Fetch it for those exact shapes. Discovery/management endpoints (/tools, /usage-statistics, pipelines, …) aren't in it — use the MCP/REST discovery tools for those.
• https://docs.tamarind.bio/llms.txt — documentation index; every page has a .md form (e.g. docs.tamarind.bio/tamarind/batch.md, /tamarind/api.md, /tamarind/pipelines.md).
• Live tool discovery — GET /tools (REST) or MCP getAvailableTools + getJobSchema(jobType) are the source of truth for what tools exist and their parameters.

This skill teaches the surface + the non-obvious behaviors those sources don't spell out (see the reference files). When in doubt about a shape, fetch openapi.yaml.

When to use this skill

Use Tamarind when the user wants to:

• Predict structure of a protein, complex, or protein-ligand system (AlphaFold, Boltz-2, Chai-1, ESMFold2, Chai/Boltz cofolding)
• Design proteins or binders (RFdiffusion, BoltzGen, BindCraft, ProteinMPNN/LigandMPNN inverse folding)
• Design or characterize antibodies/nanobodies (sequence generation, humanization, developability, immunogenicity)
• Dock small molecules to a protein (DiffDock, Autodock Vina) or predict binding affinity
• Generate MSAs for downstream folding
• Run molecular dynamics or other biophysical workflows on managed GPUs
• Batch-screen many sequences or designs through the same tool
• Chain tools into pipelines (e.g. design → fold → score) using the output of one job as the input of the next

This skill is the right fit when the work should run on Tamarind's managed cloud rather than on a local install. For purely local cheminformatics or one-off sequence I/O, use a local library (RDKit, BioPython) instead.

Access and authentication

1. Sign in at app.tamarind.bio and create an API key from the account/API settings.
2. Authenticate every REST request with the x-api-key header.
3. Never hardcode the key. Read it from the TAMARIND_API_KEY environment variable or a .env file (use python-dotenv). Never commit keys to source control.

Pricing: Every user gets 10 free jobs. For larger usage, contact [email protected] to purchase a subscription.