developer-tools

Dock AI

dock-ai

by dock-ai

Dock AI: Resolve business domains to discover MCP endpoints for real-world entities quickly and securely.

Discover MCP endpoints for real-world entities by resolving business domains.

github stars

2

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Remote — zero setupMaps business domains to MCP endpoints

best for

  • / AI agents needing to interact with specific businesses
  • / Discovering booking systems for restaurants and hotels
  • / Finding MCP connectors for real-world services

capabilities

  • / Resolve business domains to find available MCP connectors
  • / Discover which services integrate with restaurants, hotels, and other businesses
  • / Get MCP server endpoints for real-world entities
  • / Retrieve business location and capability information

what it does

Discovers MCP servers that can interact with specific businesses by looking up their domains in a registry.

about

Dock AI is an official MCP server published by dock-ai that provides AI assistants with tools and capabilities via the Model Context Protocol. Dock AI: Resolve business domains to discover MCP endpoints for real-world entities quickly and securely. It is categorized under developer tools.

how to install

You can install Dock AI in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.

license

MIT

Dock AI is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Dock AI MCP

MCP server for Dock AI - discover MCP endpoints for real-world entities.

What is this?

Dock AI is a registry that maps businesses to their MCP connectors. This MCP server allows AI agents to discover which MCP servers can interact with a given entity (restaurant, hotel, salon, etc.) by querying the Dock AI registry.

Hosted Version

Use the hosted version at https://connect.dockai.co/mcp - no installation required.

{
  "mcpServers": {
    "dock-ai": {
      "url": "https://connect.dockai.co/mcp"
    }
  }
}

Self-Hosting

Deploy to Vercel

Deploy with Vercel

Run locally

# Using uvx
uvx dock-ai-mcp

# Or install and run
pip install dock-ai-mcp
dock-ai-mcp

The server starts on http://0.0.0.0:8080/mcp.

Tools

resolve_domain

Check if an MCP connector exists for a business domain.

Input:

  • domain (string): The business domain to resolve (e.g., "example-restaurant.com")

Output:

{
  "domain": "example-restaurant.com",
  "entities": [
    {
      "name": "Example Restaurant",
      "path": null,
      "location": { "city": "Paris", "country": "FR" },
      "mcps": [
        {
          "provider": "booking-provider",
          "endpoint": "https://mcp.booking-provider.com",
          "entity_id": "entity-123",
          "capabilities": ["reservations", "availability"],
          "verification": { "level": 2, "method": "dual_attestation" }
        }
      ]
    }
  ],
  "claude_desktop_config": {
    "mcpServers": {
      "booking-provider": { "url": "https://mcp.booking-provider.com/mcp" }
    }
  }
}

Examples

Example 1: Restaurant Reservation

User: "Book a table at Gloria Osteria Paris"

Agent: [searches web for "Gloria Osteria Paris official website"]
       -> Finds domain: gloria-osteria.com
       [calls resolve_domain("gloria-osteria.com")]
       -> Gets MCP endpoint for SevenRooms
       -> Connects to the MCP server
       -> Books the table

Example 2: Hotel Booking

User: "I need a room at The Hoxton in London"

Agent: [searches web for "The Hoxton London website"]
       -> Finds domain: thehoxton.com
       [calls resolve_domain("thehoxton.com")]
       -> Gets MCP endpoints for available booking providers
       -> Uses the MCP to check availability and book

Example 3: Business with No MCP Yet

User: "Book at Le Paris Paris restaurant"

Agent: [calls resolve_domain("leparisparis.fr")]
       -> Response shows pending_providers: [{ "provider": "thefork", ... }]
       -> Informs user: "This restaurant uses TheFork for reservations,
          but TheFork hasn't published an MCP connector yet.
          You can book directly on TheFork's website."

Support

Privacy

This MCP server queries the Dock AI registry API to resolve domains. No user data is collected or stored. See our Privacy Policy.

License

MIT

FAQ

What is the Dock AI MCP server?
Dock AI is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Dock AI?
This profile displays 75 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

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

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

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

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ 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.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.875 reviews
  • Pratham Ware· Dec 28, 2024

    According to our notes, Dock AI benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Neel Mensah· Dec 24, 2024

    Dock AI reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Nikhil Bansal· Dec 24, 2024

    Dock AI is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Dhruvi Jain· Dec 20, 2024

    Dock AI reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Neel Abebe· Dec 20, 2024

    Dock AI has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Mateo Menon· Dec 12, 2024

    Dock AI has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Isabella Mehta· Dec 8, 2024

    I recommend Dock AI for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Amina Mensah· Dec 8, 2024

    Strong directory entry: Dock AI surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Tariq Nasser· Dec 4, 2024

    According to our notes, Dock AI benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Harper Bansal· Nov 27, 2024

    Dock AI reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

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