Life sciences intelligence, unified — publications, trials, drugs, genes, regulatory approvals, and patents in one cross-linked connector
Add new capabilities to Claude beyond text generation
Example: Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example: Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example: Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Time estimate: 15-60 minutes depending on server complexity
Prerequisites
SNOMED CT Terminology
Search, validate, and expand SNOMED CT concepts, directly from SNOMED International
Cortellis Regulatory Intelligence
Trusted Regulatory Answers, by Clarivate Cortellis
Clinical Trials
Access ClinicalTrials.gov data
Rhizome AI
Know what your regulator thinks
AdisInsight
Pharmaceutical drug & clinical trial intelligence
EDEN by Basecamp Research
Design antibiotics and prioritise vaccine targets against drug-resistant pathogens using EDEN, Basecamp Research's biological foundation model
We wired Amass Connector into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
We evaluated Amass Connector against two servers with overlapping tools; this profile had the clearer scope statement.
Useful MCP listing: Amass Connector is the kind of server we cite when onboarding engineers to host + tool permissions.
Amass Connector reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Amass Connector has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
I recommend Amass Connector for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Amass Connector is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
According to our notes, Amass Connector benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Strong directory entry: Amass Connector surfaces stars and publisher context so we could sanity-check maintenance before adopting.
We wired Amass Connector into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
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Manual configuration
{
"mcpServers": {
"amass": {
"url": "https://mcp.amass.tech/mcp"
}
}
}Sign in: Required.
Life sciences intelligence, unified — publications, trials, drugs, genes, regulatory approvals, and patents in one cross-linked connector
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.