Refua MCP Server

MCP server exposing strict, typed Refua tools for Boltz2 folding/affinity and BoltzGen design workflows.

Protocol target: MCP spec revision 2025-11-25.

Install

pip install refua[cuda] # remove [cuda] if you don't need gpu support
pip install refua-mcp

ADMET predictions are optional; install refua[admet] to enable them:

pip install refua[admet]

Clinical trial simulation is optional; install the clinical extra:

pip install "refua-mcp[clinical]"

Data catalog/query/source-validation tools are optional; install the data extra:

pip install "refua-mcp[data]"

Preclinical planning/scheduling/bioanalysis/CMC tools are optional; install the preclinical extra:

pip install "refua-mcp[preclinical]"

WetLab, benchmark, regulatory, and deployment tools are optional:

pip install "refua-mcp[wetlab,bench,regulatory,deploy]"

Install the full project tool surface with:

pip install "refua-mcp[ecosystem]"

OpenTelemetry spans/metrics are optional:

pip install "refua-mcp[observability]"

Boltz2 and BoltzGen require model/molecule assets. If you don't have them, refua can download them for you automatically:

python -c "from refua import download_assets; download_assets()"

• Boltz2: uses ~/.boltz by default. Override via tool boltz.cache_dir if needed.
• BoltzGen: uses the bundled HF artifact by default. Override via tool boltzgen.mol_dir if needed.

MCP Clients

Claude Code

Add the server to your Claude Code MCP config (macOS: ~/Library/Application Support/Claude/claude_code_config.json, Linux: ~/.config/claude/claude_code_config.json). This uses the default assets (~/.boltz for Boltz2 and the bundled BoltzGen artifact). Merge with any existing mcpServers entries:

{
  "mcpServers": {
    "refua-mcp": {
      "command": "python3",
      "args": ["-m", "refua_mcp.server"]
    }
  }
}

Codex

Register the server with the Codex CLI (uses default asset locations):

codex mcp add refua-mcp -- python3 -m refua_mcp.server

List configured servers with:

codex mcp list

If the server is slow to boot (for example on first import of heavy ML deps), raise the startup timeout in your Codex config.toml:

[mcp_servers.refua-mcp]
startup_timeout_sec = 30

Transport And Security

Default transport is stdio. You can run HTTP transports with runtime env vars:

REFUA_MCP_TRANSPORT=streamable-http python -m refua_mcp.server

Supported transport modes:

• REFUA_MCP_TRANSPORT=stdio|sse|streamable-http
• REFUA_MCP_HOST / REFUA_MCP_PORT
• REFUA_MCP_MOUNT_PATH

Security/runtime controls:

• REFUA_MCP_ENABLE_DNS_REBINDING_PROTECTION=true|false
• REFUA_MCP_ALLOWED_HOSTS=host1,host2
• REFUA_MCP_ALLOWED_ORIGINS=https://origin1,https://origin2
• REFUA_MCP_AUTH_TOKENS=token1,token2 (static bearer tokens for HTTP transports)
• REFUA_MCP_TASK_TIMEOUT_SECONDS
• REFUA_MCP_QUEUE_TIMEOUT_SECONDS

Tools

• refua_validate_spec: validate and normalize a request without running folding/affinity.
• refua_fold: run fold/design workflows with typed entities and constraints.
• refua_affinity: run affinity-only predictions.
• refua_antibody_design: focused antibody entrypoint (antibody + optional context_entities).
• refua_protein_properties: compute sequence-based protein properties via Refua's ProteinProperties API.
• refua_data_list (optional): list datasets from refua-data catalog.
• refua_data_fetch (optional): fetch one dataset into local cache.
• refua_data_materialize (optional): materialize one dataset into parquet parts.
• refua_data_query (optional): query filtered rows from materialized parquet data.
• refua_data_validate_sources (optional): validate catalog source URLs/API endpoints.
• refua_job: check status/results for background jobs.
• refua_admet_profile (optional): run model-based ADMET predictions for SMILES strings (requires refua[admet]).
• refua_clinical_simulator (optional): run the refua-clinical simulator and optional workup (requires refua-mcp[clinical]).
• refua_preclinical_templates (optional): fetch default study + sample templates and curated references (requires refua-mcp[preclinical]).
• refua_preclinical_plan (optional): generate GLP tox/pharmacology study planning payloads.
• refua_preclinical_schedule (optional): generate in vivo operational schedules.
• refua_preclinical_bioanalysis (optional): run bioanalytical ETL/QC and simple NCA summaries.
• refua_preclinical_workup (optional): generate integrated preclinical workups with optional bioanalysis.
• refua_preclinical_cmc_templates (optional): fetch CMC starter templates and references.
• refua_preclinical_cmc_plan (optional): generate formulation/process/QbD/validation CMC planning outputs.
• refua_preclinical_batch_record (optional): generate electronic batch record templates.
• refua_preclinical_stability_plan (optional): generate stability study schedules.
• refua_preclinical_stability_assess (optional): assess stability results against criteria.
• refua_preclinical_release_assess (optional): evaluate release decisions from batch/stability evidence.
• refua_wetlab_providers (optional): list wet-lab automation providers.
• refua_wetlab_validate_protocol (optional): validate canonical wet-lab protocol payloads.
• refua_wetlab_compile_protocol (optional): compile protocols for a provider.
• refua_wetlab_run_protocol (optional): create dry-run or queued wet-lab protocol runs.
• refua_wetlab_run_status (optional): list/fetch/cancel wet-lab runs and build run lineage.
• refua_wetlab_lms_get / refua_wetlab_lms_post (optional): access the WetLab LMS resource API.
• refua_bench_init, refua_bench_run, refua_bench_compare, refua_bench_gate, refua_bench_baseline (optional): benchmark and regression-gate workflows.
• refua_regulatory_bundle, refua_regulatory_verify, refua_regulatory_summary, refua_regulatory_checklist (optional): regulatory evidence bundle operations.
• refua_deploy_plan, refua_deploy_render (optional): deployment planning and artifact rendering.

All major tools expose strict JSON schemas, including discriminated entity unions by type and typed output schemas.

Output-format notes:

• structure_output_format: canonical values are cif or bcif; mmcif is accepted as a compatibility alias for cif.
• feature_output_format: use torch or npz when writing feature files. If json is provided with a file output request, the server normalizes it to npz and reports a warning.
• If feature_output_path ends with .json, the server normalizes it to .npz for feature file export.
• Fold/design responses include a warnings list when compatibility normalization is applied.

Input-compatibility notes:

• For compatibility with some MCP clients, entities, constraints, antibody, and context_entities also accept JSON-encoded strings and will be normalized server-side.

Execution-policy notes:

• refua_fold and refua_antibody_design block exploratory names by default (for example sanity_*, *_probe, schema_*, smoke_*) to avoid costly preflight runs.
• If an exploratory run is intentionally needed, set allow_exploratory_run=true.
• Asynchronous fold/affinity/design tools accept queue_timeout_seconds (optional).

Error-contract notes:

• Tool errors return a structured payload with error.code, error.message, optional error.hint, and error.retryable.

Resources And Templates

• refua://capabilities (resource): runtime feature flags, protocol revision, transport/security config summary.
• refua://recipes/index (resource): lists canonical recipe names.
• refua://recipes/{recipe_name} (resource template): returns concrete tool/args examples.
• refua://protein-properties/index (resource): lists available protein property names/groups.
• refua://protein-properties/group/{group_name} (resource template): lists property names in a group.
• refua://protein-properties/property/{property_name} (resource template): property metadata.

Completion support:

• refua://recipes/{recipe_name} completions for recipe names.
• refua://protein-properties/group/{group_name} completions for group names.
• refua://protein-properties/property/{property_name} completions for property names.

Recipe names:

• fold_protein_ligand
• affinity_only
• antibody_design
• protein_properties
• clinical_simulation (optional; available when refua-clinical is installed)
• preclinical_plan (optional; available when refua-preclinical is installed)
• preclinical_workup (optional; available when refua-preclinical is installed)
• preclinical_cmc_plan (optional; available when refua-preclinical is installed)
• preclinical_cmc_release (optional; available when refua-preclinical is installed)
• data_validate_sources (optional; available when refua-data is installed)
• wetlab_protocol_run (optional; available when refua-wetlab is installed)
• bench_init (optional; available when refua-bench is installed)
• regulatory_verify (optional; available when refua-regulatory is installed)
• deploy_plan (optional; available when refua-deploy is installed)

Workflow

Recommended call sequence:

1. Read refua://recipes/index and optionally a recipe template.
2. Read refua://capabilities for runtime support and limits.
3. For sequence-only property analysis, call refua_protein_properties.
4. Call refua_validate_spec to catch schema/logic issues before expensive runs (deep_validate=true for asset-backed construction checks).
5. Execute refua_fold, refua_affinity, refua_antibody_design, refua_clinical_simulator (optional), refua_wetlab_* (optional), or the refua_preclinical_* tools (optional).
6. For long runs, set async_mode=true and poll refua_job.

Examples

Fold protein + ligand with optional affinity:

{
  "tool": "refua_fold",
  "args": {
    "name": "protein_ligand",
    "entities": [
      {"type": "protein", "id": "A", "sequence": "MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQ"},
      {"type": "ligand", "id": "lig", "smiles": "CCO"}
    ],
    "constraints": [
      {"type": "pocket", "binder": "lig", "contacts": [["A", 5], ["A", 8]]}
    ],
    "affinity": {"binder": "lig"},
    "admet": true
  }
}

Affinity-only:

{
  "tool": "refua_affinity",
  "args": {
    "name": "protein_ligand_affinity",
    "entities": [
      {"type": "protein", "id": "A", "sequence": "MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQ"},
      {"type": "ligand", "id": "lig", "smiles": "CCO"}
    ],
    "binder": "lig"
  }
}

Antibody-focused design:

{
  "tool": "refua_antibody_design",
  "args": {
    "name": "ab_design",
    "antibody": {
      "type": "antibody",
      "ids": ["H", "L"],
      "heavy_cdr_lengths": [12, 10, 14],
      "light_cdr_lengths": [10, 9, 9]
    },
    "context_entities": [
      {"type": "protein", "id": "A", "sequence": "MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQ"}
    ]
  }
}

Validate only (no run):

{
  "tool": "refua_validate_spec",
  "args": {
    "action": "fold",
    "entities": [
      {"type": "protein", "id": "A", "sequence": "MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQ"},
      {"type": "ligand", "id": "lig", "smiles": "CCO"}
    ]
  }
}

ADMET predictions:

{
  "tool": "refua_admet_profile",
  "args": {
    "smiles": "CCO",
    "include_scoring": true
  }
}

Protein properties:

{
  "tool": "refua_protein_properties",
  "args": {
    "sequence": "MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQ",
    "groups": ["basic"],
    "include_catalog": true
  }
}

Clinical simulation (optional):

{
  "tool": "refua_clinical_simulator",
  "args": {
    "trial_id": "small_molecule_phase2",
    "replicates": 80,
    "include_workup": true,
    "include_replicates": false
  }
}

Preclinical workup (optional):

{
  "tool": "refua_preclinical_workup",
  "args": {
    "seed": 7,
    "lloq_ng_ml": 1.0,
    "use_template_rows_when_missing": true,
    "include_references": true
  }
}

Preclinical CMC release assessment (optional):

{
  "tool": "refua_preclinical_release_assess",
  "args": {
    "batch_results": {
      "assay_percent": 99.0,
      "content_uniformity_av": 9.8,
      "dissolution_q30_percent": 92.0,
      "total_impurities_percent": 0.7,
      "water_content_percent": 1.5,
      "appearance_score": 5.0
    },
    "include_references": true
  }
}

Note: DNA/RNA entities are supported for Boltz2 folding only (BoltzGen does not accept DNA/RNA entities).

Long-Running Jobs

For runs that exceed the tool-call timeout, set async_mode=true and poll sparingly (for example every 30-120 seconds) or follow recommended_poll_seconds from refua_job.

{
  "tool": "refua_fold",
  "args": {
    "async_mode": true,
    "entities": [...]
  }
}

Then poll:

{
  "tool": "refua_job",
  "args": {
    "job_id": "..."
  }
}

For queued/running jobs, the response includes recommended_poll_seconds plus queue and estimate metadata (queue_position, queue_depth, average_runtime_seconds, estimated_start_seconds, estimated_remaining_seconds). Set include_result=true once complete to fetch results. Set cancel=true in refua_job to cancel queued/running jobs.

Long-poll support:

{
  "tool": "refua_job",
  "args": {
    "job_id": "...",
    "wait_for_terminal_seconds": 300,
    "cancel": false,
    "include_result": true
  }
}

Experimental MCP Tasks

This server enables MCP experimental task support (tasks/get, tasks/result, tasks/list, tasks/cancel) and advertises task execution support for refua_validate_spec, refua_fold, refua_affinity, refua_antibody_design, and refua_admet_profile. refua_clinical_simulator and refua_preclinical_templates / refua_preclinical_plan / refua_preclinical_schedule / refua_preclinical_bioanalysis / refua_preclinical_workup / refua_preclinical_cmc_templates / refua_preclinical_cmc_plan / refua_preclinical_batch_record / refua_preclinical_stability_plan / refua_preclinical_stability_assess / refua_preclinical_release_assess are also task-enabled when installed.

If your client supports task-augmented tool calls, prefer tasks for long-running operations. Task cancellation (tasks/cancel) is wired to background job cancellation. Otherwise, continue with async_mode=true + refua_job.