| name | patsnap-pharma-intelligence |
| description | Patsnap Pharma Intelligence MCP for AI agents. Search clinical trials, drugs, patents, papers, deals, FDA labels and more via 28 specialized tools. |
| homepage | https://open.patsnap.com/marketplace/mcp-servers/pharma-intelligence |
| metadata | {"author":"Patsnap","category":"Life Science","version":"1.0.0","requires":{"mcp_endpoint":"https://connect.patsnap.com/096456/logic-mcp?apikey=YOUR_API_KEY"}} |
Setup
Get your API Key at https://open.patsnap.com
Patsnap Pharma Intelligence
This skill connects your AI agent to Patsnap's Pharma Intelligence MCP server — the most comprehensive pharmaceutical data layer available for AI agents.
With this skill, your agent gains the ability to perform professional-grade pharmaceutical research: from identifying drug targets and searching clinical trials, to analyzing licensing deals and reviewing FDA labels.
Prerequisites
This skill requires the Patsnap Pharma Intelligence MCP server to be configured in your environment:
{
"mcpServers": {
"pharma_intelligence": {
"url": "https://connect.patsnap.com/096456/logic-mcp?apikey=YOUR_API_KEY",
"type": "streamableHttp"
}
}
}
Get your API key at open.patsnap.com.
For the full list of available tools and input parameters, refer to the official MCP server documentation:
open.patsnap.com/marketplace/mcp-servers/pharma-intelligence
Instructions for AI Agents
Step 1: Always Normalize Entities First
Before executing any search or fetch operation, always call ls_ner_nor_normalize on the user's input text. This tool identifies and normalizes targets, drugs, diseases, companies, mechanisms of action (MoA), patent numbers, and clinical trial IDs — returning the internal IDs required by all downstream tools.
Do not skip this step. Raw user text must be resolved to Patsnap internal IDs for accurate retrieval.
Step 2: Choose the Right Tool for the Task
This MCP provides 28 tools organized across these domains:
- Drug & Pipeline: search and fetch drug assets, licensing and collaboration deals
- Clinical Trials: structured search, semantic search, and published results
- Scientific Literature: paper search, vector search, and translational medicine
- Patents & Regulatory: patent fetch, FDA label semantic search
- Market & Epidemiology: disease data, HEOR, financial reports, epidemiology
- Real-Time News: semantic news search and full article fetch
For the complete tool list and input parameters, see:
open.patsnap.com/marketplace/mcp-servers/pharma-intelligence
Step 3: Fetch Full Records When Needed
Search tools return summary results with IDs. When the user needs complete details, always follow up with the corresponding _fetch tool (e.g., after ls_drug_search, call ls_drug_fetch with the returned IDs).
Step 4: Synthesize and Structure Your Output
After retrieving data, present findings in a structured, professional format:
- Lead with key findings: Summarize the most relevant results first
- Cite sources: Always include drug names, trial IDs, paper titles, or patent numbers
- Highlight gaps: If data is limited, acknowledge it and suggest alternative search strategies
- Use tables for comparing multiple drugs, trials, or deals side by side
Example Workflows
Biomarker Investigation
ls_ner_nor_normalize → extract target/disease entities
ls_paper_search → find supporting academic evidence
ls_clinical_trial_search → identify trials using this biomarker
ls_patent_fetch → check IP landscape
Competitive Drug Landscape
ls_ner_nor_normalize → normalize disease/target
ls_drug_search → enumerate competing assets
ls_drug_deal_search → identify recent BD activity
ls_news_vector_search → surface latest developments
Target Intelligence
ls_ner_nor_normalize → resolve target ID
ls_drug_search → find all drugs modulating this target
ls_paper_vector_search → retrieve mechanistic literature
ls_clinical_trial_search → map clinical development activity
Resources