About biomedmcp
biomedmcp gives AI agents cited access to biomedical records and research sources, for researchers investigating genes, targets, variants, and trials. Its focused workflows preserve source identifiers and distinguish missing or partial evidence from negative findings.
Key features
- 01Search biomedical literature and records
- 02Build target dossiers and evidence notebooks
- 03Retrieve gene, variant, and trial evidence
- 04Inspect article full text and tables
- 05Identify partial or unavailable source data
Use cases
- 01Investigate a gene target and tissue expression
- 02Find genetic studies related to a research question
- 03Review registered clinical trial records
- 04Check variant evidence without mixing identifiers
MCP support
Provides biomedical research tools and cited source records to MCP clients over Streamable HTTP, with local server and command-line options also described.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://biomedmcp.unibiointelligence.com/mcpclaude mcp add --transport http unibio-intelligence-biomedmcp https://biomedmcp.unibiointelligence.com/mcp{"mcpServers":{"unibio-intelligence-biomedmcp":{"type":"http","url":"https://biomedmcp.unibiointelligence.com/mcp"}}}Open in Cursor{"servers":{"unibio-intelligence-biomedmcp":{"type":"http","url":"https://biomedmcp.unibiointelligence.com/mcp"}}}Open in VS Code{"mcpServers":{"unibio-intelligence-biomedmcp":{"type":"http","url":"https://biomedmcp.unibiointelligence.com/mcp"}}}{"mcpServers":{"unibio-intelligence-biomedmcp":{"serverUrl":"https://biomedmcp.unibiointelligence.com/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project READMEbiomedmcp
BioMedMCP gives your AI agent cited access to biomedical sources, including PubMed, UniProt, ClinicalTrials.gov, ChEMBL, Open Targets and GTEx, so its answers point to records you can check.
Start with a research question
Try this with your MCP client:
Build an evidence notebook on LDL-receptor biology and cholesterol lowering. Start with a human LDLR target dossier, inspect tissue expression, then find PCSK9 genetic studies. Separate observations, intervention results and open questions. Cite the records you read and identify any unavailable sources.
Connect to https://biomedmcp.unibiointelligence.com/mcp using Streamable HTTP
and sign in when prompted. For a local server, install the
Python distribution or build from this checkout; see connection options.
Run the same investigation locally
Use Python 3.13+ in an activated virtual environment:
python -m pip install biomedmcp==0.2.4
UBI_PROFILE=local biomedmcp build_dossier '{"workflow":"target_dossier","focus":"LDLR","species":9606}'
The single Python distribution includes all source adapters. From a source
checkout, uv sync --frozen installs the locked environment; prefix commands
with uv run --frozen when using it.
These focused calls can fill gaps in the notebook:
UBI_PROFILE=local biomedmcp get_record '{"entity":"gene","id":"LDLR","species":9606,"sections":["expression"]}'
UBI_PROFILE=local biomedmcp search_literature '{"query":"PCSK9","filters":{"source":"pubmed","date_from":"2024-01-01"}}'
UBI_PROFILE=local biomedmcp get_variant_evidence '{"id":"PCSK9 R46L"}'
Check each response's source, species and identifiers before combining records; a partial or unavailable section is a gap, not a negative result. Follow its continuation and recovery links to see more than the preview.
Choose the next question
| Research task | Where to start |
|---|---|
| Separate target observations from causal claims | Evidence investigations |
| Inspect an allele without conflating transcript or genome build | Typed call examples |
| Read a paper's accessible text and tables | get_record with entity: "article" and sections: ["fulltext"] |
| Examine registered studies | trial_search; inspect each study's submitted record |
| Reproduce a local analysis | Synthetic study walkthrough |
Connect a local agent
UBI_PROFILE=local biomedmcp-server --transport http --host 127.0.0.1 --port 8000
Use http://127.0.0.1:8000/mcp, or configure a stdio client using the
connection guide. The call reference covers
exact JSON arguments; result handling explains partial
results and evidence boundaries.
Some sources need a key or installed dataset. Run biomedmcp diagnose and consult
source access. Keep credentials in environment variables
or client secret storage. A failed source doesn't mean there is no evidence.
The integration code uses Apache-2.0. Retrieved data retains its source terms. See notices, release notes and contributing.
Acknowledgements
We gratefully acknowledge support from Anthropic's AI for Science rare disease research grants.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.