How do I use kegg-mcp-server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@kegg-mcp-server search pathways for glycolysis in human" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

kegg-mcp-server

by Lucas-Servi

Overview Schema Related Servers Score Discussions

Python

Hybrid

kegg-mcp-server-python

PyPI Python 3.11–3.14 License: MIT

An unofficial Python Model Context Protocol (MCP) server for the KEGG bioinformatics database. It exposes 34 tools, 9 resource templates, and 4 guided prompts to any MCP-compatible client (Claude Desktop, Claude Code, Cursor, etc.). Developed by Elytron Biotech.

Built with FastMCP, returns structured Pydantic JSON (not raw text), and includes per-operation TTL caching, request retry with exponential backoff, KEGG-friendly concurrency limits, structured JSON stderr logging, and batch helpers out of the box. No API key required -- uses the free KEGG REST API.

Responses are token-aware by default: get_*_info tools return a compact EntrySummary (entry id, name, class, description, counts of linked entities) unless you pass detail_level="full". Errors are returned as a typed ErrorResult the model can reason about, not raised as exceptions.

Note: This is a community non-official project and is not affiliated with or endorsed by KEGG or Kanehisa Laboratories.

Quick start

With `uvx` (no install)

uvx kegg-mcp-server

With pip

pip install kegg-mcp-server
kegg-mcp-server

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "kegg": {
      "command": "uvx",
      "args": ["kegg-mcp-server"]
    }
  }
}

OS	Path
macOS	`~/Library/Application Support/Claude/claude_desktop_config.json`
Windows	`%APPDATA%\Claude\claude_desktop_config.json`
Linux	`~/.config/Claude/claude_desktop_config.json`

Claude Code

claude mcp add kegg-mcp-server -- uvx kegg-mcp-server

Or install as a plugin (includes skill metadata):

claude plugin install Lucas-Servi/kegg-mcp-server-python

MCPB bundle (Claude Desktop, no Python required)

Download the latest .mcpb from the releases page and drag it onto Claude Desktop. The bundle vendors all Python dependencies and runs with Claude Desktop's embedded Python.

What's included

34 Tools

Category	Tools	Examples
Database	`get_database_info`, `list_organisms`	Get KEGG release stats, list all ~26k organisms
Pathways	`search_pathways`, `get_pathway_info`, `get_pathway_genes`, `get_pathway_compounds`, `get_pathway_reactions`	Search by keyword, get full pathway details
Genes	`search_genes`, `get_gene_info`, `get_gene_orthologs`	Find genes in any organism, cross-species orthologs
Compounds	`search_compounds`, `get_compound_info`, `get_compound_reactions`	Search by name/formula/mass, find reactions
Reactions	`search_reactions`, `get_reaction_info`	Equation, enzymes, pathways for any reaction
Enzymes	`search_enzymes`, `get_enzyme_info`	EC number lookup, substrates, genes
Diseases	`search_diseases`, `get_disease_info`	Disease genes, drugs, pathways
Drugs	`search_drugs`, `get_drug_info`, `get_drug_interactions`	Drug targets, DDI screening
Modules	`search_modules`, `get_module_info`	Functional module definitions
Orthology	`search_ko_entries`, `get_ko_info`	KEGG Orthology entries
Glycans	`search_glycans`, `get_glycan_info`	Glycan composition, reactions
BRITE	`search_brite`, `get_brite_info`	Functional hierarchies
Cross-database	`batch_entry_lookup`, `convert_identifiers`, `find_related_entries`	Bulk fetch (up to 50), ID mapping (UniProt, NCBI, ChEBI, PubChem)
Visualization	`render_pathway_ascii`	ASCII art rendering of pathway topology (chain or grid mode)

9 Resource Templates

Direct URI-based access to KEGG entities:

kegg://pathway/{pathway_id}        e.g. kegg://pathway/hsa00010
kegg://gene/{gene_id}              e.g. kegg://gene/hsa:1956
kegg://compound/{compound_id}      e.g. kegg://compound/C00002
kegg://reaction/{reaction_id}      e.g. kegg://reaction/R00756
kegg://disease/{disease_id}        e.g. kegg://disease/H00004
kegg://drug/{drug_id}              e.g. kegg://drug/D00001
kegg://organism/{org_code}         e.g. kegg://organism/hsa
kegg://pathway/{pathway_id}/ascii  e.g. kegg://pathway/hsa00010/ascii
kegg://search/{database}/{query}   e.g. kegg://search/compound/glucose

4 Guided Prompts

Prompt	Arguments	What it does
`pathway_enrichment_analysis`	`gene_list`, `organism`	Maps a gene list to KEGG IDs, aggregates pathway associations, identifies enriched pathways
`drug_target_investigation`	`drug_name`	Drug lookup, target identification, pathway mapping, DDI screening
`metabolic_pathway_comparison`	`pathway_id`, `organisms`	Compares gene/compound content of a pathway across species
`visualize_pathway`	`pathway_id`, `organism`	Renders pathway as ASCII art (chain + grid), annotates key steps

ASCII Pathway Renderer

The render_pathway_ascii tool converts KEGG pathway topology (from KGML XML) into LLM-friendly ASCII text. Two styles are available:

Chain mode (default) — linear reaction flow:

Glycolysis / Gluconeogenesis (hsa)
====================================

[alpha-D-Gl~] ──R01786──▶ [beta-D-Gl~] ──R01600──▶ [beta-D-F~]

Grid mode — 2D spatial layout using KGML coordinates:

Glycolysis / Gluconeogenesis (hsa)
====================================

  [Glc]────────▶[G6P]────────▶[F6P]
                  │
                  ▼
                [6PG]

Legend:
  [Glc] = alpha-D-Glucose (cpd:C00267)
  [G6P] = D-Glucose 6-phosphate (cpd:C00092)

Transport options

# stdio (default -- for Claude Desktop, Claude Code, uvx)
kegg-mcp-server

# Streamable HTTP (for web/API deployment)
kegg-mcp-server --transport streamable-http --host 0.0.0.0 --port 8080

# python -m also works
python -m kegg_mcp_server

Development

git clone https://github.com/Lucas-Servi/kegg-mcp-server-python
cd kegg-mcp-server-python
pip install -e ".[dev]"

# Run tests
pytest tests/ -v

# Lint
ruff check src/ tests/

# Debug with MCP Inspector
mcp dev kegg-mcp-server

Project structure

src/kegg_mcp_server/
  server.py       FastMCP instance, lifespan (httpx client + TTL cache), CLI
  client.py       KEGGClient: async KEGG REST with retry/backoff + KEGG-politeness semaphore
  cache.py        Per-op TTL cache (info 24h, list 1h, entry ops 5min)
  parsers.py      KEGG flat-file and tab-delimited response parsers + summarize_flat_entry
  errors.py       KEGGAPIError exception type
  logging.py      JSON stderr logger (stdout is reserved for MCP stdio framing)
  resources.py    8 MCP resource templates
  prompts.py      3 bioinformatics workflow prompts
  models/         Pydantic models for all KEGG entity types + EntrySummary + ErrorResult
  tools/          13 tool modules, each with a register(mcp) function; _common.py has the
                  @kegg_tool error-boundary decorator and shared READ_ONLY annotations

Author

Developed by Lucas Servi (lucasservi@gmail.com) at Elytron Biotech using Claude Code.

Acknowledgments

Based on Augmented-Nature/KEGG-MCP-Server -- the original TypeScript implementation that served as the foundation for this Python rewrite
KEGG -- Kyoto Encyclopedia of Genes and Genomes (Kanehisa Laboratories)
Model Context Protocol -- Anthropic's open protocol for LLM tool use

License

MIT -- see LICENSE.

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

2wRelease cycle

3Releases (12mo)

Resources

GitHub Repository

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