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MCP server · AI

Refua MCP

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

Unclaimed MIT last commit 7 months ago refuamodel-context-protocolmcpaidrug-discoveryprotein-folding
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Scored 7 days ago · breakdown

About Refua MCP

Refua MCP is an MCP server published by agentcures in the AI category: mCP server exposing strict typed Refua tools for Boltz2 folding, affinity prediction, and BoltzGen design workflows.

Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.

Install

From source
git clone https://github.com/agentcures/refua-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Tools (8)

feature_output_formatuse `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.

Parameters not published.

refua_affinityrun affinity-only predictions.

Parameters not published.

refua_antibody_designfocused antibody entrypoint (`antibody` + optional `context_entities`).

Parameters not published.

refua_foldrun fold/design workflows with typed entities and constraints.

Parameters not published.

refua_jobcheck status/results for background jobs.

Parameters not published.

refua_protein_propertiescompute sequence-based protein properties via Refua's `ProteinProperties` API.

Parameters not published.

refua_validate_specvalidate and normalize a request without running folding/affinity.

Parameters not published.

structure_output_formatcanonical values are `cif` or `bcif`; `mmcif` is accepted as a compatibility alias for `cif`.

Parameters not published.

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Releases

v0.8.0v0.8.0
v0.7.1v0.7.1
v0.7.0v0.7.0
v0.6.0v0.6.0
v0.5.2v0.5.2

README

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]"

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

pip install "refua-mcp[preclinical]"

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_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.

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)

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), 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.

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Refua MCP

How do I install Refua MCP?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Refua MCP safe to use with an AI agent?

Its trust score is 62 out of 100 (good). It passes 2 of the 3 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Refua MCP still maintained?

The last commit was 7 months ago. That's long enough that you should check whether the maintainer is responding to issues before depending on it.