DBCLS
Model Context Protocol Server for Life Sciences Research
TogoMCP is a comprehensive Model Context Protocol (MCP) server developed by DBCLS that provides LLM agents with seamless access to a vast ecosystem of life sciences databases. It integrates over 20 major biological and biomedical databases, enabling AI assistants like Claude, ChatGPT, and Gemini to help researchers query, explore, and integrate complex biological data using natural language.
Through SPARQL queries, RDF data exploration, and ID conversion services, TogoMCP bridges the gap between AI assistants and the rich data landscape of life sciences. Whether you're a biologist exploring disease–protein associations, a chemist searching for drug candidates, or a data scientist integrating information across multiple domains, TogoMCP provides a powerful toolkit for knowledge discovery.
Query proteins, genes, chemicals, diseases, pathways, and more across 20+ integrated databases including UniProt, PubChem, ChEMBL, PDB, Reactome, ClinVar, and others — all through a single MCP endpoint.
Built on Semantic Web technologies. TogoMCP exposes SPARQL endpoints from the RDF Portal, enabling precise, structured queries with rich cross-references between datasets.
Powered by TogoID, the server converts identifiers across 65+ biological databases — including cross-category conversions (e.g., disease IDs → gene IDs) with semantic relationship annotations.
Designed for integration with LLM-based assistants. Compatible with Claude Desktop, ChatGPT, and Gemini CLI. No bioinformatics expertise required — use natural language to explore data.
TogoMCP is described in the following preprint. Please cite it if you use TogoMCP in your research.
Kinjo, A. R., Yamamoto, Y., Bustamante-Larriet, S., Labra-Gayo, J.-E., & Fujisawa, T. (2026). TogoMCP: Natural Language Querying of Life-Science Knowledge Graphs via Schema-Guided LLMs and the Model Context Protocol. bioRxiv. https://doi.org/10.64898/2026.03.19.713030
The following examples illustrate how AI assistants powered by TogoMCP can tackle complex life sciences research questions by orchestrating queries across multiple databases.
The system loaded the ChEMBL schema via get_MIE_file, ran parallel target searches across CVD areas (RAAS, coagulation, lipid pathways, ion channels), then issued comprehensive SPARQL queries against the EBI endpoint to retrieve approved (Phase 4) inhibitors anchored on MeSH disease IRIs (cco:hasMesh) and human single-protein targets. It used TogoID to bridge ChEMBL target IDs to UniProt accessions and compiled an interactive classification dashboard.
The system loaded the UniProt MIE to confirm the up:enzyme predicate and the mandatory up:reviewed 1 filter, then ran a single aggregating SPARQL query against the SIB endpoint, anchored on up:organism <…/taxonomy/9606>. EC class was extracted from the enzyme IRI by stripping the prefix and taking the first digit before the dot, giving counts of unique protein–EC-class associations across all seven EC classes.
The system loaded the MIEs for ChEBI, ChEMBL, and PubChem, then ran five SPARQL queries: ChEBI biological roles under the CHEBI:33245 natural-product hierarchy via OWL restrictions; ChEMBL approved-drug counts grouped by ATC therapeutic area; PubChem MW distribution for FDA-approved drugs (via the sio:SIO_000008 hub-and-spoke pattern); a cross-graph ChEMBL × ChEBI join confirming NP-derived approved drugs; and a NP pharmacological-role query with mass statistics. Results were synthesised into an interactive dashboard.
Connect TogoMCP to your AI assistant in minutes. Choose your platform below.
https://togomcp.rdfportal.org/mcpclaude_desktop_config.json.{
"mcpServers": {
"togomcp": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://togomcp.rdfportal.org/mcp"]
}
}
}
MCP connectors in ChatGPT are currently available for Business/Enterprise plans only.
https://togomcp.rdfportal.org/mcpTogoMCP uses Streamable HTTP transport (not SSE). Configure your settings.json as follows:
{
"mcpServers": {
"togomcp": {
"httpUrl": "https://togomcp.rdfportal.org/mcp"
}
}
}
Save the file — Gemini CLI will automatically detect the new MCP server on next launch.
TogoMCP integrates over 20 major life sciences databases, covering proteins, genes, chemicals, diseases, pathways, taxonomy, and more.
TogoMCP exposes a rich set of tools for searching, querying, and converting life sciences data.
get_MIE_file first to understand the database schema and available properties.TogoMCP works excellently in combination with these complementary MCP servers for richer research workflows.
PubDictionaries provides text annotation services for biomedical literature, helping identify and map biological entities such as genes, proteins, diseases, and chemicals in text.
The PubMed MCP server provides access to the world's largest biomedical literature database, enabling article search, metadata retrieval, and full-text access from PubMed Central.
The Ontology Lookup Service (OLS4) from EMBL-EBI provides access to biomedical ontologies, enabling standardization of terminology and exploration of hierarchical relationships between biological concepts.
Explore the ecosystem of tools and organizations behind TogoMCP.
The NBDC RDF Portal is a comprehensive repository of semantic life sciences data developed by DBCLS and NBDC. It hosts 21+ RDF datasets comprising over 45.5 billion triples, all quality-reviewed for interoperability and SPARQL queryability. TogoMCP's SPARQL queries run against this portal's unified endpoint.
TogoID is an identifier conversion service by DBCLS that bridges 65+ life science databases. Unlike traditional converters, it supports cross-category conversions (e.g., disease IDs → gene IDs) with semantic relationship annotations. TogoMCP's ID conversion tools are powered by TogoID's API.
The Database Center for Life Science (DBCLS) is a Japanese research institute under ROIS, founded in 2007. It conducts research on database integration, Semantic Web technologies, and bioinformatics resources. DBCLS organizes the annual BioHackathon and monthly SPARQLthon events, and develops tools like TogoID, TogoTV, and TogoMCP.
The TogoMCP source code is open and available on GitHub. Contributions, bug reports, and feature requests are welcome.