kegg-mcp-server-python

kegg-mcp-server-python

An unofficial Python Model Context Protocol (MCP) server for the KEGG bioinformatics database. It exposes 35 tools, 9 resource templates, and 4 guided prompts to any MCP-compatible client (Claude Desktop, Claude Code, Cursor, etc.). Developed by Elytron Biotech.

Built on the official MCP Python SDK v2 (MCPServer), returns structured Pydantic JSON (not raw text), and includes per-operation TTL caching, request retry with exponential backoff, a three-request-per-second rate limit, structured JSON stderr logging, and batch helpers out of the box. No API key is required.

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". List- and mapping-shaped outputs are capped at 100 items and report the full count plus truncated. Failures are MCP tool errors (isError: true) whose text is a typed ErrorResult JSON (code, retryable, hint) the model can reason about.

0.5.0 changes output shapes: failures (including not-found) are now isError: true instead of a normal result; convert_identifiers maps each source ID to a list of targets; link/ortholog/pathway-gene/DDI outputs are capped with truncated; batch_entry_lookup returns summaries unless detail_level="full"; logging is configured with --log-level / --log-tracebacks instead of environment variables.

0.6.0 adds draw_pathway_map: a PNG pathway map with gene boxes coloured by KO/EC groups, redrawn from KGML (new dependency: Pillow). See Pathway map images.

Usage notice: This is a community project and is not affiliated with or endorsed by KEGG or Kanehisa Laboratories. KEGG states that its REST API is for academic use by academic users; non-academic users must follow KEGG's linked non-academic-use guidance. Users are responsible for ensuring that their use complies with those terms.

---

Quick start

With uvx (no install)

uvx kegg-mcp-server

With pip

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

Requires the MCP Python SDK v2 (mcp>=2,<3, protocol revision 2026-07-28). Versions up to 0.3.1 ran on the 1.x SDK; because mcp 2.0 removed mcp.server.fastmcp, that is a breaking dependency change, which is why this is 0.4.0 rather than a patch. Nothing changes for clients — an mcp 2.x server answers every earlier protocol revision from the same app, so a host still on the 1.x SDK connects unchanged and negotiates 2025-11-25.

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 slash commands, agent, and skill):

claude plugin marketplace add Lucas-Servi/kegg-mcp-server-python
claude plugin install kegg-mcp-server@kegg-mcp-server

Or, in one step (Claude Code v2.1.292+), pointing install at the marketplace directly:

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

The plugin starts a local (stdio) MCP server, so it works in Claude Code, Cowork, and Claude Desktop, but not in the claude.ai web app.

The plugin bundles:

Type	Name	Description
Command	/kegg <query>	Quick search across all KEGG databases
Command	/kegg-pathway <id>	Pathway deep-dive with ASCII visualization
Command	/kegg-drug <name>	Drug targets, pathways, and interactions
Agent	kegg-bioinformatics	Auto-invoked for biological pathway/gene/drug questions
Skill	kegg-analysis	Multi-step workflow guide (enrichment, comparison, investigation)

MCPB bundle (Linux x86-64 only, no Python install required)

The release bundle is built specifically for Linux x86-64 and CPython 3.12 because it vendors native dependencies. Download the linux-x86_64-py312.mcpb artifact from the releases page and drag it onto Claude Desktop. On macOS or Windows, use the cross-platform uvx, pip, or Claude Code plugin installation above.

---

What's included

35 Tools

Category	Tools	Examples
Database	get_database_info, list_organisms	Get KEGG release stats, search the ~12k organisms by code or name
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 (level counts by default; detail_level="full" for the capped tree). Takes any id form KEGG emits — br:ko00001, ko00001, or the bare 00001 from search_brite
Cross-database	batch_entry_lookup, convert_identifiers, find_related_entries	Bulk fetch (up to 50), ID mapping within one kind — genes ↔ UniProt/NCBI, chemistry ↔ ChEBI/PubChem
Visualization	render_pathway_ascii, draw_pathway_map	ASCII art rendering of pathway topology (chain or grid mode); a PNG map with gene boxes coloured by KO/EC groups (e.g. one per genome)

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

---

Pathway map images

draw_pathway_map draws a KEGG map as a PNG and colours its gene boxes by up to 8 highlight groups, for example one per genome:

{"pathway_id": "map00010",
 "highlight": {"Strain A": ["K00844", "K01810", "EC:4.1.2.13"],
               "Strain B": ["K01810", "2.7.1.11"]}}

• Every box is split into one stripe per group: coloured when the group has one of the box's KOs, grey when it doesn't. A KO without a direct match is coloured through EC numbers when one item carries every EC KEGG links to that KO (listed as matched_by_ec, a less specific match than a KO). An item may hold one gene's ids separated by spaces, e.g. a GenBank db_xref string as is, so a bifunctional KO isn't lit by two unrelated single-function genes.
• The image is redrawn from KGML (boxes, compounds, reaction lines, links to other maps) with Pillow; KEGG's own map bitmap is not fetched or redistributed. The footer credits KEGG.
• The result is a text block with the summary JSON (also structuredContent) and an image block (image/png). The summary lists, per group, the map KOs found and boxes coloured, and per box its KOs and the groups that have it, so an agent can check the figure without vision.
• map, ko, organism (eco00020, drawn as the KO reference map) and bare (00010) ids are accepted. Global/overview maps (011xx, 012xx) are refused with code: "global_map".
• The drawing code is importable without MCP: kegg_mcp_server.pathway_map.build_pathway_map( kegg_client, pathway_id, groups) returns the PNG bytes and the same summary.

---

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

# Logging (stderr, JSON): verbosity and full tracebacks
kegg-mcp-server --log-level DEBUG --log-tracebacks

---

Data handling

• The only network destination is the public KEGG REST API at https://rest.kegg.jp (all tools, resources, and the ASCII renderer's KGML fetch go there). Queries you make (IDs, search terms) are sent to KEGG; nothing is sent anywhere else, and there is no telemetry.
• Responses are cached in memory only (per-operation TTL) and discarded when the server exits; nothing is written to disk.
• Logs are structured JSON on stderr only, on your machine.
• No API key or account, and the server reads no environment variables of its own (logging is set by CLI flags). The HTTP client (httpx) honours the standard proxy and CA-bundle variables (HTTPS_PROXY, NO_PROXY, SSL_CERT_FILE, …) so it works behind corporate proxies.
• The uvx launcher downloads the pinned kegg-mcp-server package and its dependencies from PyPI on first run.

---

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       MCPServer 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, 64 MiB budget (info 24h, list 1h, entry ops 6h)
  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    9 MCP resource templates
  prompts.py      4 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.