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Health and biology · MCP server

Plant Genomics: MCP server, setup and security

Plant Genomics is an open-source MCP server published on GitHub that lets an AI agent look up plant genomic loci and query multiple sources in batches. Its repository has 8 stars and its last commit is from October 24, 2026 and it is licensed under MIT.

Actively maintained

What Plant Genomics does

According to its repository: “Plant genomics locus lookup across Ensembl Plants, Phytozome, UniProtKB, KEGG, STRING-DB, NCBI BLAST and more, with batch and cross-source queries.”

The Model Context Protocol (MCP) is a standard plug between an AI agent and an outside service: once the server is connected, its tools show up in the agent, which decides when to call them. Plant Genomics is listed under Health and biology, a category of 37 servers in the directory, where it ranks #31 by stars.

Topics declared by the repository: bioinformatics, ensembl-plants, genomics, kegg, llm-tools, plant-genomics.

Installing and connecting Plant Genomics

Distribution modes declared in the official MCP registry:

  • PyPI package (Python, started with uvx or pip)

It works with any MCP-compatible client (Claude Desktop, Claude Code, Cursor, VS Code, Codex and most recent agents). You add one entry to the client's MCP configuration: server name, start command or URL, environment variables. Project language: Python. Listed systems: macOS, Windows, Linux.

Security: what to check

Connecting an MCP server means installing software that talks straight to your agent: it runs with your rights and the model trusts its tool descriptions. The risk therefore depends on what it can touch and how far its code can be trusted.

None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to Plant Genomics. That does not replace reading the code.

Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.

Project activity and maintenance

Created on May 22, 2026, the musharna/plant-genomics-mcp repository has 8 stars and 0 forks, with 2 open issues. It has more stars than 22% of the servers in the directory. It received changes this month. Version published in the registry: 1.29.3 (October 17, 2026).

Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.

MedplumMedplum : 2.8K2.8KPyscnPyscn : 1.1K1.1KBiomcpBiomcp : 662662Apple health MCP serverApple health MCP server : 279279HealthChainHealthChain : 229229Walk kcalWalk kcal : 195195FHIR MCP Server (wso2)FHIR MCP Server (wso2) : 136136TotemTotem : 135135Plant GenomicsPlant Genomics : 88
GitHub stars of the most followed servers in the category (log scale); Plant Genomics in orange. Checked October 25, 2026.

Verdict

Plant Genomics is a reasonable choice; check the points below before connecting it.

Strengths

  • Active project: recent commit
  • Listed in the official MCP registry
  • Permissive licence (MIT)

Limitations

  • Few visible users

Frequently asked questions

How do I install Plant Genomics?

Plant Genomics is distributed as PyPI package (Python, started with uvx or pip). Add it to your client's MCP configuration (Claude Desktop, Cursor, VS Code…) following the README of musharna/plant-genomics-mcp.

Is Plant Genomics free?

The code is published under the MIT licence and can be used free of charge.

Is Plant Genomics safe?

No risk signal found (system access, secrets, licence, abandonment). As with any MCP server, keep rights minimal and read the code before sensitive use.

Is it an official server?

Nothing says so: it is a project published by musharna on GitHub. Check who maintains it before giving it access.

What are the alternatives to Plant Genomics?

In the same category: Medplum, Pyscn, Biomcp, and FHIR MCP Server (wso2). Medplum and Pyscn score higher on our grid.

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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score