MCP Registry Actor

Discover, search, and explore Model Context Protocol (MCP) servers from the OpenConductor registry - the largest curated collection of MCP servers for AI agents.

What is this Actor?

The MCP Registry Actor provides AI agents and developers with programmatic access to the OpenConductor registry, enabling discovery and exploration of 70+ MCP servers across multiple categories including memory management, file systems, databases, API integrations, and more.

Key Features

• 🔍 Advanced Search: Find MCP servers by keyword, category, or tags
• 📊 Trending Servers: Discover what's popular in the MCP ecosystem
• 📂 Category Browsing: Explore servers by category (memory, filesystem, database, etc.)
• 📈 Popularity Metrics: Access real-time stats including GitHub stars and install counts
• ✅ Verified Servers: Filter by verified and featured servers
• 🔗 Complete Metadata: Get repository info, installation commands, and documentation links

Use Cases

For AI Agents

• Autonomously discover and recommend MCP servers based on user needs
• Build context-aware tool recommendations
• Stay updated on trending tools in the ecosystem

For Developers

• Integrate MCP server discovery into your applications
• Build recommendation engines for developer tools
• Track ecosystem growth and trends
• Research competitive analysis in the MCP space

For Data Analysis

• Analyze MCP ecosystem trends
• Track server popularity over time
• Identify gaps in the tooling landscape

Input Configuration

The Actor supports multiple operation modes:

Mode: Search (Default)

Search for MCP servers by query, category, or tags.

{
  "mode": "search",
  "query": "memory",
  "category": "memory",
  "tags": ["ai", "storage"],
  "limit": 10
}

Mode: Details

Get detailed information about a specific server.

{
  "mode": "details",
  "slug": "openmemory"
}

Mode: Trending

Discover trending servers over a time period.

{
  "mode": "trending",
  "trendingPeriod": "7d"
}

Mode: Categories

List all available categories.

{
  "mode": "categories"
}

Mode: Popular

Get the most popular servers in a category.

{
  "mode": "popular",
  "category": "memory",
  "limit": 10
}

Input Parameters

Parameter	Type	Required	Default	Description
mode	string	No	"search"	Operation mode: search, details, trending, categories, or popular
query	string	No	""	Search term for finding servers (search mode)
category	string	No	null	Filter by category (search/popular modes)
tags	array	No	null	Filter by tags (search mode)
limit	integer	No	10	Maximum results (1-100)
slug	string	Yes*	-	Server identifier (required for details mode)
trendingPeriod	string	No	"7d"	Time period: 24h, 7d, or 30d (trending mode)

* Required only when mode is "details"

Output

The Actor outputs structured JSON data containing:

Search Mode Output

{
  "mode": "search",
  "query": "memory",
  "category": "memory",
  "totalResults": 15,
  "servers": [
    {
      "id": "359f402d-64c6-42ed-b7d5-e19868d9b824",
      "slug": "openmemory",
      "name": "OpenMemory",
      "tagline": "Hierarchical memory for AI agents",
      "category": "memory",
      "tags": ["memory", "storage", "semantic-search", "AI"],
      "repository": {
        "url": "https://github.com/openai/openmemory",
        "owner": "openai",
        "name": "openmemory",
        "stars": 1640
      },
      "stats": {
        "stars": 1640,
        "installs": 847,
        "popularity": 95
      },
      "installation": {
        "npm": "npm install -g openmemory"
      },
      "verified": true,
      "featured": true
    }
  ],
  "pagination": {
    "page": 1,
    "limit": 10,
    "total": 15,
    "totalPages": 2
  }
}

Details Mode Output

Returns comprehensive information about a single server including documentation URLs, maintainer info, and detailed installation instructions.

Trending Mode Output

{
  "mode": "trending",
  "period": "7d",
  "servers": [
    {
      "name": "OpenMemory",
      "growth": {
        "percentage": 25,
        "absolute": 120
      },
      "stats": {
        "stars": 1640,
        "installs": 847
      }
    }
  ]
}

Available Categories

• memory: Memory & State Management
• filesystem: File System Operations
• database: Database Integrations
• api: API Integrations
• search: Search & Discovery
• communication: Communication Tools
• monitoring: Monitoring & Observability
• development: Development Tools
• custom: Custom Integrations

Examples

Example 1: Find All Memory-Related Servers

{
  "mode": "search",
  "category": "memory",
  "limit": 20
}

Example 2: Search for Database Servers

{
  "mode": "search",
  "query": "postgres",
  "category": "database"
}

Example 3: Get Trending Servers This Week

{
  "mode": "trending",
  "trendingPeriod": "7d"
}

Example 4: Get Details About a Specific Server

{
  "mode": "details",
  "slug": "github-mcp"
}

Example 5: List All Categories

{
  "mode": "categories"
}

API Integration

This Actor uses the OpenConductor API to fetch real-time data about MCP servers. The registry is updated regularly with new servers, stats, and trending information.

Data Freshness

• Server metadata: Updated in real-time
• GitHub stats: Refreshed every 24 hours
• Install counts: Updated hourly
• Trending data: Calculated every 6 hours

Performance

• Average execution time: 2-5 seconds
• Timeout: 30 seconds
• Rate limiting: Respects OpenConductor API limits
• Caching: Results can be cached on Apify platform

Error Handling

The Actor includes comprehensive error handling:

• Network failures are retried automatically
• Invalid input parameters return descriptive error messages
• API errors are logged with full context
• Timeout protection for slow responses

Privacy & Data

• No personal data is collected
• All data is publicly available from OpenConductor
• Server statistics are anonymized
• Complies with GitHub API ToS

Related Resources

• OpenConductor Website
• OpenConductor CLI
• Model Context Protocol Specification
• MCP Documentation

Support

For issues, feature requests, or questions:

• GitHub Issues: openconductor/issues
• Email: hello@openconductor.ai
• Twitter: @openconductor

Changelog

Version 1.0.0 (2025-11-20)

• Initial release
• Support for search, details, trending, categories, and popular modes
• Comprehensive input/output schemas
• Real-time data from OpenConductor API
• Full error handling and logging

License

MIT License - see LICENSE for details.

Author

Built with ❤️ by the OpenConductor team.

Part of the Apify $1M Challenge - empowering developers to build the future of AI automation.