MCP Servers

Open-source Model Context Protocol servers that provide AI agents with secure, structured access to specialized data sources and APIs. Built for production use with comprehensive documentation and testing.

What is the Model Context Protocol?

The Model Context Protocol (MCP) is an open standard created by Anthropic that enables AI models to securely connect to external data sources and tools. Think of it as a universal adapter that lets AI agents access databases, APIs, and services in a standardized, secure way.

MCP servers expose specific capabilities (called "tools") that AI agents can discover and use. Each tool has a clear description, defined inputs, and structured outputs—making it easy for AI to understand what's available and how to use it.

Secure by Design

Built-in authentication, rate limiting, and permission controls. AI agents can only access what you explicitly allow.

Standardized Interface

One protocol works across all AI clients. Write once, use everywhere—from Claude Desktop to custom applications.

Production Ready

Error handling, logging, and observability built in. Deploy with confidence knowing your integrations are reliable.

How MCP Works

AI Client
Claude, Cursor, Custom App
MCP Server
Exposes Tools & Resources
Database
API
Files
1

Discovery

AI client connects to MCP server and discovers available tools, resources, and prompts.

2

Tool Invocation

AI agent decides which tools to call based on user request and tool descriptions.

3

Data Access

MCP server executes the tool, queries the data source, and returns structured results.

4

Response

AI agent processes the data and presents it to the user in natural language.

Works With Your Favorite Tools

Claude Desktop

Anthropic's desktop app

Cursor IDE

AI-powered code editor

Claude.ai

Web interface

Custom Apps

Your own integrations

Available Servers

Drug Safety MCP

@sineai/drug-safety-mcp
Available Now

Comprehensive pharmacovigilance toolkit providing access to FDA adverse event data (FAERS), drug labels, and recall information. Built for medical monitors, regulatory affairs, and drug safety professionals.

17 tools
MIT License

Key Features

  • FDA FAERS adverse event database access
  • Drug label information and boxed warnings
  • Pediatric and geriatric safety profiles
  • Signal detection and trend analysis
  • Recall history and enforcement actions
  • Compare safety profiles across drugs
  • Search by drug class or indication

Use Cases

  • Pharmacovigilance signal detection
  • Clinical trial protocol development
  • Competitive intelligence analysis
  • Regulatory submission preparation

Quick Install

npm install @sineai/drug-safety-mcp

See the GitHub repository for complete setup instructions, configuration options, and usage examples.

Research Evidence MCP

@sineai/research-evidence-mcp
Available Now

Scientific literature search and evidence synthesis toolkit. Search PubMed and Springer Nature, merge and rank results, generate citation-backed evidence briefs, and export references in BibTeX/RIS formats.

9 tools
MIT License
Available via MCP Gateway

Key Features

  • PubMed search with date and article type filters
  • Springer Nature search with Open Access detection
  • Intelligent merge and ranking algorithm
  • Evidence briefs with citation-first approach
  • BibTeX and RIS citation export
  • Related articles discovery
  • Automatic quota management for Springer API

Use Cases

  • Systematic literature reviews
  • Clinical research background
  • Evidence-based decision making
  • Academic paper writing
  • Medical education content

Access

https://mcp.sineai.co/research/mcp

Connect via our MCP Gateway. Contact us for access credentials and integration support.

More MCP Servers Coming Soon

We're actively developing additional MCP servers for specialized domains. Follow us on GitHub to stay updated on new releases.

Getting Started with MCP

MCP servers work with any MCP-compatible client, including Claude Desktop, Cursor IDE, and custom applications. Installation is straightforward—just add the server to your MCP configuration.

1

Install

Install the MCP server via npm or clone from GitHub

2

Configure

Add to your MCP client configuration file

3

Use

AI agents can now access the server's tools

Need a custom MCP server?

We build production-ready MCP servers for specialized data sources, APIs, and workflows. Let's discuss your requirements.