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  3. Flowproof MCP
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Flowproof MCP

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Run reproducible bioinformatics pipelines (Nextflow) from an AI assistant, with verifiable Workflow Run RO-Crate provenance (container digests, tool versions, input/output checksums). pip install flowproof-mcp

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "ajibadedapo-flowproof-mcp": {
      "command": "uvx",
      "args": [
        "flowproof-mcp"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives📂 More in Biology, Medicine and Bioinformatics

Documentation Overview

FlowProof

PyPI Python License: MIT

Reproducible bioinformatics pipeline execution over the Model Context Protocol (MCP), with verifiable provenance.

FlowProof lets an AI assistant run a bioinformatics pipeline and hand back results whose provenance can be independently verified: pipeline version, container digests, tool versions, parameters, and SHA-256 checksums of every input and output, emitted as a Workflow Run RO-Crate.

It fills the layer the MCP-for-bioinformatics ecosystem is missing. Data access already has MCP servers (BioMCP); analysis planning already has AI agents (Biomni, AutoBA). The gap is reliable, trustworthy execution, which needs orchestration and provenance discipline. That is what FlowProof provides.

Why it exists

An AI that "runs an analysis for you" is only useful if you can trust the result. FlowProof makes every run reproducible and independently checkable, so an AI-driven result is not a black box: it ships with the exact recipe and checksums to reproduce it byte-for-byte.

Status

FlowProof is working and installable today (pip install flowproof-mcp). The pipeline registry, execution backends, and RO-Crate provenance are complete and covered by tests, and the MCP server exposes six tools (list, describe, run, status, results, provenance). It ships with two execution backends: a zero-dependency backend for development and CI, and a Nextflow backend that runs real pipelines.

Install

Code
uv sync

Using FlowProof

FlowProof works two ways. Both let an AI assistant run pipelines for you; you never touch a terminal after setup.

Local (recommended for real data)

Runs on your own machine, so your data never leaves it and your compute runs the pipelines. No token needed.

Add this to your MCP client config (Claude Desktop: claude_desktop_config.json; Cursor: MCP settings):

config.json
{
  "mcpServers": {
    "flowproof": {
      "command": "uvx",
      "args": ["flowproof-mcp"]
    }
  }
}

Then just ask your assistant: "list the FlowProof pipelines" or "run the ONT assembly on this file". Runs are written under ~/.flowproof/runs (override with FLOWPROOF_RUNS_DIR).

Cloud (instant, no install)

Connect your client to the hosted server. Nothing to install; the cloud runs it. Uses a bearer token today (per-user keys and OAuth are on the roadmap):

config.json
{
  "mcpServers": {
    "flowproof": {
      "url": "https://flowproof.specvista.com/mcp/",
      "headers": { "Authorization": "Bearer YOUR_TOKEN" }
    }
  }
}

Run the server directly

Code
flowproof                        # stdio (local, default)
FLOWPROOF_TRANSPORT=http flowproof   # HTTP server on :8000

Tools

ToolPurpose
list_pipelinesRegistered pipelines with id, description, read type
describe_pipelineInputs, parameters, outputs for a pipeline
run_pipelineExecute a pipeline reproducibly, returns a run id
get_run_statusStatus of a run
get_resultsOutput file manifest with checksums
get_provenanceThe verifiable Workflow Run RO-Crate record

Pipelines (seed)

idRead typeAnalysis
ont-read-statslongOxford Nanopore read statistics (QC); optional Flye assembly. Runs on a built-in sample if you provide no input.
variant-call-shortshortShort-read QC to germline variant calling (nf-core/sarek)
rnaseqshortRNA-seq quantification: QC, trimming, alignment, gene counts (nf-core/rnaseq)
fetchngsshortFetch raw reads and metadata from public archives, SRA/ENA/GEO (nf-core/fetchngs)
viralreconshortViral genome reconstruction and variant calling from amplicon data (nf-core/viralrecon)

New pipelines register by manifest; the server does not change.

Try it instantly: ask your assistant to "run ont-read-stats" with no input, and FlowProof runs the bundled Oxford Nanopore sample end to end and returns a verifiable provenance crate, no data or reference genome required.

Backends

  • MockBackend: deterministic, dependency-free. Used for development and tests.
  • NextflowBackend: runs nextflow run with a container profile. Requires Nextflow and Docker.

Provenance

Every run emits ro-crate-metadata.json following the Workflow Run RO-Crate profile, capturing the workflow and version, container images, resolved tool versions, exact parameters, and SHA-256 checksums of all inputs and outputs.

Develop

Code
PYTHONPATH=src uv run --with pytest --no-project python -m pytest tests/ -q

Architecture

See DESIGN.md.

Cite

If you use FlowProof in your research, please cite the archived software release:

Ajibade, H. A. (2026). FlowProof: reproducible bioinformatics pipeline execution over the Model Context Protocol with verifiable provenance (v0.1.2). Zenodo. https://doi.org/10.5281/zenodo.21932977

A machine-readable CITATION.cff is included, so GitHub shows a "Cite this repository" button with BibTeX and APA formats.

bibtex
@software{flowproof,
  author    = {Ajibade, Hammed Adedapo},
  title     = {FlowProof: reproducible bioinformatics pipeline execution over the Model Context Protocol with verifiable provenance},
  year      = {2026},
  version   = {0.1.2},
  publisher = {Zenodo},
  doi       = {10.5281/zenodo.21932977},
  url       = {https://github.com/ajibadedapo/flowproof-mcp}
}

Read the full README →View source on GitHub →

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Frequently Asked Questions about Flowproof MCP

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "flowproof-mcp": { "command": "npx", "args": ["-y", "ajibadedapo/flowproof-mcp"] } }

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Technical Specs & Signals

Category📂Biology, Medicine and Bioinformatics
More technical detailsExpand ▾
TransportSTDIO
RuntimeNode.js
Last updatedSep 7, 2026
Views0
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36Quality signal: Fair · 36/100How this signal is calculated ▾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20
Documentation & tools18/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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