BioContext Knowledgebase
This MCP server provides AI assistants with unified access to biomedical databases and research tools through a single interface, built by the BioContextAI team using Python with FastMCP and designed to eliminate the need for custom integrations with each biomedical resource. The implementation offers over 20 specialized tools covering protein databases (UniProt, AlphaFold, Human Protein Atlas), genomics resources (Ensembl, KEGG), literature search (Europe PMC, Google Scholar), clinical data (ClinicalTrials.gov, OpenFDA), and ontologies (Gene Ontology, EFO, ChEBI), with both self-hosted deployment options and a hosted service at mcp.biocontext.ai. Built with comprehensive test coverage, Docker support, and integration with the BioContextAI Registry for community tool discovery, it serves researchers needing programmatic access to biomedical data, bioinformatics teams requiring standardized database queries, and AI applications that need verified biomedical information without managing multiple API integrations.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Repository
- github.com/biocontext-ai/knowledgebase-mcp
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve BioContext Knowledgebase from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.