BioHarbor

Name: BioHarbor
Author: danielLuo2

by danielLuo2version 0.1.6i★ –iRuns on your computer

Registry nameio.github.danielLuo2/bioharbor

Install

Overview

Description from the maker (original English)

Run real bioinformatics from your AI agent. Reliable, reproducible, on your own GPUs.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "bioharbor": {
      "command": "uvx",
      "args": [
        "bioharbor",
        "serve"
      ]
    }
  }
}

Run this in your terminal

claude mcp add bioharbor -- uvx bioharbor serve

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "bioharbor": {
      "command": "uvx",
      "args": [
        "bioharbor",
        "serve"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "bioharbor": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "bioharbor",
        "serve"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account danielLuo2, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32718 servers in this category
Published to the registry more recently than 58% of the other 32718 servers in this category
Basic checks equal to or better than 100% of the other 32718 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is BioHarbor safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.6) reached the registry 28 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, MemberVault MCP by usefulapi

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

BioHarbor

Run real bioinformatics from your AI agent. Reliable, reproducible, on your own GPUs.

🧪 Alpha (v0.1). Sequence tools, homology search (MMseqs2) and structure prediction

(ESMFold, validated on RTX 5090) work. Feedback welcome — see the roadmap.

BioHarbor is an MCP server that lets AI agents such as Claude, Cursor and Codex *execute* bioinformatics tools — not just look things up. Agents ask for an analysis; BioHarbor validates the input, schedules it on a GPU with room, records exactly how it ran, and hands back a compact, agent-readable summary.

Why another bio MCP server?

Most bio MCP servers wrap databases (UniProt, PDB, PubMed…). Use them — BioHarbor complements them by running the compute:

	Database MCP servers	BioHarbor
Runs real analyses (search, fold, cluster)	❌	✅
Validates inputs before burning GPU time	❌	✅
GPU-aware queue, polite on shared GPUs	❌	✅
Long jobs return a `job_id` instead of timing out	❌	✅
Compact summaries + files on disk (saves tokens)	❌	✅
Provenance for every run, export to a pipeline	❌	✅ (export: planned)

Quick start

pip install bioharbor

bioharbor doctor # checks Python, GPUs, workspace, tools bioharbor setup-db swissprot # reference database for search_homologs (needs MMseqs2) bioharbor install # shows how to connect Claude, Cursor or Codex

For structure prediction on a GPU: pip install "bioharbor[esmfold]" — see docs/gpu-setup.md (RTX 50xx needs a CUDA 12.8+ PyTorch).

Connect your agent

BioHarbor is a standard MCP server, so it works with any MCP client. One command sets up the popular ones (it writes an absolute path, so GUI apps find it even outside your venv):

Client	Set up
Claude Code	`claude mcp add bioharbor -- bioharbor serve`
Claude Desktop	`bioharbor install claude-desktop --write`, then restart the app
Cursor	`bioharbor install cursor --write`, or
Codex (CLI, IDE extension, app)	`codex mcp add bioharbor -- bioharbor serve`, or `bioharbor install codex --write`
Biomni (Stanford's biomedical agent)	`agent.add_mcp(...)`; see docs/use-with-biomni.md
Anything else	run `bioharbor serve` (stdio) or `bioharbor serve --http` (Streamable HTTP)

Long-running tools return a job_id within ~20 s instead of blocking, so they stay within every client's tool-call timeout.

Step-by-step setup (local or on a GPU server, with troubleshooting): docs/connect-clients.md.

Then ask your agent something like:

*Find the longest ORF in this contig, translate it, search Swiss-Prot for homologs and

predict its structure. Which regions are low confidence?*

Use it without an agent

Every tool is also a CLI command, with identical behaviour:

bioharbor tools list

bioharbor run find_orfs sequence=@contig.fa min_aa=100 --brief # human-readable bioharbor run seq_stats sequence=MKTAYIAKQRQISFVKSHFSRQ bioharbor jobs

Shared GPU server

GPUs on a lab server, agent on your laptop? Run BioHarbor on the server and reach it through an SSH tunnel; no extra port is opened on the server:

# on the GPU server

bioharbor serve --http --host 127.0.0.1 --port 8765

on your laptop, then point Cursor / Codex / Claude Code at http://127.0.0.1:8765/mcp

ssh -N -L 8765:127.0.0.1:8765 you@gpu-server

⚠️ HTTP mode has no authentication yet (on the roadmap), so keep it on 127.0.0.1 and

use the tunnel. Details: docs/connect-clients.md.

Tools

Tool	What it does	Runs
`seq_stats`	Validate sequences; type, length, GC%, molecular weight	inline
`translate_sequence`	DNA/RNA → protein, one or all six frames	inline
`find_orfs`	Longest ORFs on both strands, with coordinates	inline
`search_homologs`	MMseqs2 search (protein, or translated DNA) vs local DBs	job
`predict_structure`	ESMFold structure, pLDDT bands, low-confidence regions, pTM	job (GPU)
`scrna_pipeline`	scanpy QC → clustering → markers	planned

Runtime tools: get_job, list_jobs, cancel_job, describe_tool, list_databases, gpu_status, read_file.

How it works

Agent ──MCP──▶ validate input ─▶ inline? ──yes──▶ run ─┐

│ no ├─▶ provenance + summary ─▶ Agent ▼ │ job queue (SQLite) ─▶ GPU placement ┘ (waits politely for a GPU with free memory)

Every call is a job recorded in SQLite with params, versions, timings and GPU used, plus a provenance.json next to its outputs.
GPU placement reads live free memory and utilisation (NVML or nvidia-smi), keeps headroom, and reserves memory for jobs it has started so two jobs never grab the same space. Other users' processes are respected.
Fail fast: input, binaries and databases are checked *before* a job is queued, so a bad request never waits behind a busy GPU.
Results are agent-shaped: summary, message, files, suggestions. Errors carry a hint and a retryable flag.

Details: docs/design.md.

Writing a tool

from pydantic import BaseModel, Field

from bioharbor.registry import Resources, RunContext, tool from bioharbor.results import ToolResult

class FoldParams(BaseModel): sequence: str = Field(..., description="Protein sequence")

@tool( version="1", slow=True, resources=Resources(gpu=True, gpu_mem_gb=lambda p: 4 + len(p.sequence) / 100), ) def predict_structure(params: FoldParams, ctx: RunContext) -> ToolResult: """Predict a protein structure with ESMFold.""" ... return ToolResult(summary={"mean_plddt": 87.1}, files=["model.pdb"])

Plugins can ship tools in their own package via the bioharbor.tools entry-point group. See CONTRIBUTING.md.

License

Apache-2.0

BioHarbor

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

MemberVault MCP by usefulapi

README from the maker

BioHarbor

Why another bio MCP server?

Quick start

Connect your agent

Use it without an agent

Shared GPU server

on your laptop, then point Cursor / Codex / Claude Code at http://127.0.0.1:8765/mcp

Tools

How it works

Writing a tool

License