Surechembl MCP Server
The SureChEMBL chemical patent database MCP server provides a comprehensive toolset for patent search, chemical discovery, structural analysis, and patent intelligence research.
rating : 2.5 points
downloads : 0
What is the SureChEMBL MCP Server?
This is an intelligent tool specifically designed for chemical patent research, which can connect to the SureChEMBL database - one of the largest chemical patent databases in the world. It allows you to easily search and analyze chemical patents, discover new compounds, conduct prior art research, and analyze the relationship between chemical structures and patent claims.How to use the SureChEMBL MCP Server?
Simply through the Claude desktop application or an AI assistant that supports the MCP protocol, you can directly query chemical patent information, obtain compound data, generate chemical structure images, and perform various patent analysis tasks without writing complex code or directly accessing the database.Applicable scenarios
Chemical researchers, patent attorneys, R & D teams of pharmaceutical companies, academic researchers, and any professionals who need to access chemical patent information for innovation research or competitive analysis.Main features
Patent document search
Search for chemical patent documents by text, keywords, or patent numbers, supporting full - text search and exact matching.
Chemical substance search
Search for chemical compounds by name, SMILES structural formula, or InChI code, supporting synonym and structural similarity search.
Structure visualization
Generate chemical structure images, supporting custom sizes and formats for easy display and analysis.
Patent chemical analysis
Analyze the chemical content in patent documents, extract key compound information and annotation statistics.
Data export
Batch export chemical data in CSV or XML format for further analysis and processing.
Advanced statistical analysis
Get the frequency statistics of chemicals in the patent database and an overview of the patent chemical content.
Advantages
Access to a professional chemical patent database without programming knowledge
Integrated into AI assistants to provide a natural language interaction experience
Support for multiple chemical identifiers and search methods
Provide rich visualization functions and data analysis tools
Automatic handling of API limits and error retry mechanisms
Limitations
Dependent on the availability and response time of the SureChEMBL API
Complex queries may have a 30 - second timeout limit
Requires an internet connection to access the database service
Some advanced functions may require professional knowledge to fully utilize
How to use
Installation and configuration
Install the server via npm and configure the MCP server connection in the Claude desktop application.
Start the server
Run the server program to ensure a connection with the AI assistant.
Start querying
Ask questions related to chemical patents to the AI assistant in natural language.
Analyze the results
View the returned patent information, chemical data, and structure images.
Usage examples
New compound patent retrieval
A research team discovers a new compound and needs to check if there are any related patents.
Competitor company patent analysis
Analyze the chemical patent portfolio of a specific pharmaceutical company.
Chemical structure similarity search
Find patented compounds with similar structures to the target compound.
Frequently Asked Questions
What kind of technical background is required to use this tool?
What chemical identifier formats are supported?
Is the data updated in real - time?
Are there any usage or query limits?
Can the data be exported for further analysis?
Related resources
SureChEMBL official website
Official database website, providing more database information and usage guides
GitHub project repository
Source code and latest updates
Model Context Protocol specification
Official documentation and technical specifications of the MCP protocol
Augmented Nature official website
Official website of the development team to learn more about AI - enhanced scientific research tools

Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
15.9K
4.5 points

Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
16.9K
4.3 points

Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
44.7K
4.3 points

Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
25.0K
5 points

Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
19.4K
5 points

Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
45.3K
4.5 points

Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
15.0K
4.5 points

Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
63.7K
4.7 points




