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musharna/plant-genomics-mcp

by Various

Plant genomics MCP server — 32 tools across 11 backends (Ensembl Plants, Phytozome, UniProt, Europe PMC, QuickGO, NCBI BLAST, Gramene, KEGG, STRING-DB, ATTED-II, BAR) + cross-sourc

M

MCP

musharna/plant-genomics-mcp

Added 8 June 2026

#bioinformatics #ensembl-plants #genomics #kegg #llm-tools #mcp #model-context-protocol #plant-genomics

Overview

A Model Context Protocol server that exposes 32 plant genomics tools across 11 backends including Ensembl Plants, Phytozome, UniProt, Europe PMC, QuickGO, NCBI BLAST, Gramene, KEGG, STRING-DB, ATTED-II, and BAR. It supports stdio and Streamable-HTTP transports and can synthesize results across sources.

Best for

Best for
Developers building AI agents or pipelines that need unified access to plant genomics data

Use cases

  • Query gene annotations and sequences from multiple plant genomics databases via a single interface
  • Run BLAST searches against plant genomes and retrieve functional enrichment data
  • Cross-reference gene identifiers and pathway data across Ensembl, KEGG, and STRING-DB

Notes

A Model Context Protocol server that exposes 32 plant genomics tools across 11 backends including Ensembl Plants, Phytozome, UniProt, Europe PMC, QuickGO, NCBI BLAST, Gramene, KEGG, STRING-DB, ATTED-II, and BAR. It supports stdio and Streamable-HTTP transports and can synthesize results across sources.

0 stars on GitHub. Last updated 2026-06-07. Licensed MIT.

Use cases

  • Query gene annotations and sequences from multiple plant genomics databases via a single interface
  • Run BLAST searches against plant genomes and retrieve functional enrichment data
  • Cross-reference gene identifiers and pathway data across Ensembl, KEGG, and STRING-DB

Pros

  • Covers a wide range of major plant genomics databases in one tool
  • Supports both local stdio and HTTP streaming transports for flexible integration
  • Cross-source synthesis reduces manual data merging

Cons

  • Zero stars and no community traction yet
  • Requires running a Python MCP server, adding deployment overhead
  • Dependence on external APIs means reliability varies by backend uptime

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Covers a wide range of major plant genomics databases in one tool
  • Supports both local stdio and HTTP streaming transports for flexible integration
  • Cross-source synthesis reduces manual data merging

Cons

  • Zero stars and no community traction yet
  • Requires running a Python MCP server, adding deployment overhead
  • Dependence on external APIs means reliability varies by backend uptime