Benchling MCP (longevity-genie)

Overview

Benchling MCP (longevity-genie) provides an MCP interface to selected Benchling laboratory-data workflows. It is a third-party integration server, distinct from the Benchling platform itself; the supplied sources do not establish upstream endorsement. Its role is to let an MCP-capable AI client request existing research records through structured tools rather than interact directly with Benchling's API.

The documented inputs include a Benchling API key and domain, followed by tool arguments such as project or folder identifiers, sequence type, search text, entity-type filters, and result limits. Outputs are described as notebook entries and experimental records, DNA/RNA/protein sequences with annotations, project metadata, and matching entities. A separate MCP resource exposes API information and usage guidance. The listed tools cover retrieval and search; the excerpts do not document record creation, editing, or laboratory-instrument control.

The Python package uses FastMCP and includes the Benchling SDK among its dependencies. Its documentation describes STDIO, streamable HTTP, and SSE operation, although the README's default-transport description differs from the package entry-point mapping. Setup therefore warrants checking the selected launch path before client integration. Access requires a Benchling account with API access, and upstream API rate limits still apply. The README describes rate-limit handling, logging, and credential-dependent integration tests, but these statements are not evidence of completed testing for a particular deployment.

Key Features

• `benchling_get_entries(folder_id?, project_id?, limit?)` retrieves laboratory notebook entries with optional folder, project, and result-count filters.
• `benchling_get_sequences(sequence_type?, folder_id?, limit?)` retrieves DNA, RNA, or protein sequence records; the README describes access to sequence annotations.
• `benchling_get_projects(limit?)` retrieves projects and their metadata.
• `benchling_search(query, entity_types?, limit?)` searches Benchling entities using query text, optional entity-type restrictions, and result limits.
• `resource://benchling_api-info` provides Benchling API documentation and usage guidance through an MCP resource.
• The README documents STDIO, streamable HTTP, and SSE modes, along with API-key authentication, rate-limit response handling, and logging.

Use Cases

• Suggested evaluation: retrieve entries from a known project or folder to assess whether an AI client can locate the experimental records needed for a research discussion.
• Suggested evaluation: retrieve DNA or protein sequences from a selected folder and compare the returned records with the corresponding Benchling records.
• Suggested evaluation: search for a research term across selected entity types to assess cross-record discovery within an authorized Benchling workspace.
• Suggested evaluation: retrieve project metadata to support navigation of laboratory research projects without assuming write or automation capabilities.

How to Use

1. Read the README and confirm that entry, sequence, project, or search retrieval matches the intended workflow. Obtain a Benchling account with API access before configuring the server.
2. Review the package configuration, which declares Python 3.10 or later. Follow the README's uv-based setup guidance rather than assuming an unlisted installation route.
3. Configure BENCHLING_API_KEY and BENCHLING_DOMAIN locally as documented. Keep credentials out of shared drafts, client configuration examples, and published logs.
4. Select a transport and adapt the README's MCP-client configuration. Check the package entry points because the bare launcher mapping and README default-mode description differ.
5. Evaluate a narrow retrieval request using a known project or folder, then try a filtered search. Compare results with Benchling and inspect errors before widening access. The README describes integration tests requiring credentials; it does not establish results for your environment.