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benchling-integration

Helps your agent connect with the Benchling system. It allows automating lab data recording and managing scientific information.

What it does

This tool connects you to Benchling, a system used in labs to manage scientific data. It allows you to automate tasks like importing DNA sequences, checking inventory, or exporting information.

When to use it

  • ✓Import DNA sequences from a file into Benchling.
  • ✓Check what materials (inventory) are in a specific lab location.
  • ✓Export lists of DNA sequences with specific information.

Example of what to ask your AI

“Import the sequences from the file 'sequences.fasta' into the 'lib_example' folder.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/K-Dense-AI/scientific-agent-skills/blob/main/skills/benchling-integration/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/K-Dense-AI/scientific-agent-skills/blob/main/skills/benchling-integration/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The tool uses special code (SDK) to communicate with Benchling. You need to set up access with your credentials, and then you can ask it to perform actions like reading or writing data.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add K-Dense-AI/scientific-agent-skills --skill benchling-integration

Or download just the file:

curl -L https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/main/skills/benchling-integration/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Benchling Integration

When to use

Use this skill for Benchling registry entities, sequence imports, inventory, ELN entries, workflow tasks, apps, event-driven integrations, and warehouse analytics.

Reviewed 2026-09-30: examples target the released benchling-sdk 1.25.0 and its stable v2 API models. The current authentication guide recommends V3 for new development, while the V3 guide still describes endpoint-specific early access. Confirm your tenant's V3 availability and stability before migrating; these v2 SDK examples must not be mechanically rewritten to V3.

SDK imports, model serialization, and request construction were checked locally against 1.25.0. Tenant-dependent examples are illustrative: no authenticated requests, mutations, AWS deployment, or warehouse connection were run.

Workflow

  1. Identify the tenant, API version, identity, and permissions. Use OAuth app credentials for background integrations; use delegated authorization when acting as an individual user. See authentication.
  2. Read the relevant schema and resolve actual folder, registry, status, and dropdown IDs. Preserve sequence alphabet/topology and sample units. A valid Python model does not establish biological correctness or satisfaction of a tenant's required fields.
  3. Read a small filtered page before writing. Use typed SDK methods and check their actual parameter names; not all services share the same CRUD naming convention.
  4. Construct and serialize a representative payload. For imports, retain external IDs and returned Benchling IDs so a retry can reconcile a partial run without duplicates.
  5. Perform the requested operation and read back the result. Check terminal async status; completed polling can still mean FAILED.

Setup and a read-only query

uv pip install "benchling-sdk==1.25.0"
import os
from benchling_sdk.benchling import Benchling
from benchling_sdk.auth.client_credentials_oauth2 import ClientCredentialsOAuth2

tenant_url = os.environ["BENCHLING_TENANT_URL"].rstrip("/")
benchling = Benchling(
    url=tenant_url,
    auth_method=ClientCredentialsOAuth2(
        client_id=os.environ["BENCHLING_CLIENT_ID"],
        client_secret=os.environ["BENCHLING_CLIENT_SECRET"],
        token_url=f"{tenant_url}/oauth/token",
    ),
)
for page in benchling.dna_sequences.list(page_size=10, name_includes="plasmid"):
    for sequence in page:
        print(sequence.id, sequence.name)
    break  # deliberate first-page connectivity/permission check

A successful empty page is a valid connectivity result. It does not imply access to all projects. There is no documented v2 users/me route or SDK users.get_me().

Important SDK conventions

  • Import fields from benchling_sdk.helpers.serialization_helpers. Its input is {"field_name": {"value": value}}, including the inner value mapping.
  • Use dna_sequence_id for DNA updates and workflow_task_id for workflow updates. Workflow task creation requires a workflow_task_group_id.
  • Entry methods are create_entry, get_entry_by_id, list_entries, and update_entry.
  • list() usually returns pages; iterate twice to reach the objects. estimated_count is a property that can raise NotImplementedError, not a method or guaranteed count.
  • Moving a tube uses ContainerUpdate(parent_storage_id=...). Material transfer is a separate operation; it changes contents and quantities.
  • Register on creation with registry_id plus either entity_registry_id (a human registry identifier) or naming_strategy. Do not confuse those with the registry's ID.

Common use cases

Import FASTA sequences

Install Biopython separately (uv pip install biopython). This illustrative import creates unregistered linear DNA; choose topology and resolve collisions before running.

from Bio import SeqIO
from benchling_sdk.models import DnaSequenceCreate

for record in SeqIO.parse("sequences.fasta", "fasta"):
    payload = DnaSequenceCreate(
        name=record.id,
        bases=str(record.seq),
        is_circular=False,
        folder_id="lib_example",
    )
    created = benchling.dna_sequences.create(payload)
    print(record.id, created.id)  # persist this mapping for restart/reconciliation

Audit inventory under a location


…
FAQ

What is Benchling?

Benchling is a platform used in laboratories to organize and manage research data, such as DNA sequences, inventory, and experiments.

What is an SDK?

SDK stands for 'Software Development Kit'. It's a set of tools that helps developers create programs that interact with other systems, like Benchling.

Do I need to know how to code to use this?

Although the tool uses code behind the scenes, the goal is for you to be able to request tasks in simple language, and it will handle the technical part.

Details

Original description by the author

Benchling Python SDK and REST API integration for registry entities, inventory, ELN entries, workflows, Benchling Apps, and Data Warehouse queries. Use when automating lab data with benchling-sdk or the v2 API.

repo: K-Dense-AI/scientific-agent-skills

Popularity

GitHub stars
51k
Ranking position
#1837
License
MIT
Updated
10/15/2026

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