How to Make Your MCP App Discoverable

You built an MCP app. It works. It's useful. But nobody can find it.

Discoverability is the #1 challenge for MCP app developers. With hundreds of new apps launching every week across ChatGPT, Claude, and Gemini, standing out requires deliberate effort. This guide covers the practical steps to get your app found, tried, and adopted.

1. Nail Your App Metadata

AI platforms use your metadata to decide when to surface your app. This isn't optional — it's the foundation.

Name and Description

Your app name should be clear and specific. "DataHelper" tells nobody anything. "SQL Query Builder for PostgreSQL" tells everyone exactly what it does.

Your description has two audiences: humans browsing the directory and the AI model deciding when to invoke your tools. Write for both:

Build and run SQL queries against PostgreSQL databases.
Supports SELECT, INSERT, UPDATE, and DELETE with schema-aware autocomplete.
Ideal for data analysts who need quick database access from chat.

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Model Description

The model_description field is what the AI reads to decide if your app is relevant. Be specific about:

• What problems your app solves
• What inputs it needs
• What outputs it provides
• When it should NOT be used

Keywords for Discovery and Triggering

These fields directly control when AI platforms surface your app:

• keywords_for_discovery: Broad terms users might search ("database", "SQL", "analytics")
• keywords_for_triggering: Specific phrases that should invoke your tools ("run a query", "check the database", "analyze this data")

2. Design Clear, Well-Documented Tools

Your MCP tools are your API. Treat them like a public product.

Tool Naming

Use descriptive, action-oriented names:

❌ Bad✅ Goodqueryrun_sql_querygetDatasearch_products_by_categoryprocessconvert_image_to_png

Input Schemas

Define clear JSON schemas with descriptions for every parameter:

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "SQL query to execute (SELECT, INSERT, UPDATE, DELETE)"
    },
    "database": {
      "type": "string",
      "description": "Target database name",
      "default": "production"
    },
    "limit": {
      "type": "integer",
      "description": "Maximum rows to return (1-1000)",
      "default": 100
    }
  },
  "required": ["query"]
}

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Tool Annotations

MCP annotations help platforms understand your tools' behavior:

• readOnlyHint: Set to true for read-only tools (higher trust, more invocations)
• destructiveHint: Flag tools that modify data (platforms may add confirmation steps)
• idempotentHint: Mark tools safe to retry
• openWorldHint: Indicate tools that access external systems

3. Implement Health and Reliability

App stores increasingly factor reliability into discoverability rankings.

Transport Support

Support both MCP transport protocols for maximum compatibility:

1. Streamable HTTP (/mcp endpoint) — the modern standard
2. SSE (Server-Sent Events) — legacy but still widely used

Health Checks

Platforms periodically check your MCP endpoint. A healthy app gets priority in recommendations. Ensure your server:

• Responds to initialize within 5 seconds
• Returns accurate tools/list responses
• Handles concurrent connections gracefully
• Returns proper error codes (not 500 for invalid input)

Uptime Monitoring

Catalog systems track your uptime percentage. An app at 99.5% uptime will rank significantly higher than one at 85%. Use health check monitoring and set up alerts.

4. Optimize Your Store Presence

Logo and Branding

• Use a clear, recognizable logo (not a generic icon)
• Provide both light and dark mode variants (logo_url and logo_url_dark)
• Keep it simple — logos render at 32x32px in most contexts

Screenshots and Example Prompts

If the platform supports it, add:

• Screenshots showing your app in action
• Example prompts that demonstrate real use cases
• SEO description with natural language explaining your value proposition

Categories and Tags

Choose the most specific category that fits. An app in "DEVELOPER_TOOLS" competes with fewer apps than one in "PRODUCTIVITY".

5. Build for Multi-Store Distribution

Your app should work across all major AI platforms, not just one.

Cross-Platform Compatibility

Each platform has slightly different requirements:

PlatformTransportAuthKey ConsiderationChatGPTStreamable HTTPOAuth, API KeyWidget domain requiredClaudeSSE, Streamable HTTPNone, OAuthRegistry metadata importantGeminiStreamable HTTPOAuthGoogle ecosystem integration

Consistent Identity

Use the same app name, description, and branding across all stores. Inconsistency confuses users and fragmenting your reputation.

6. Content and SEO Strategy

Discoverability extends beyond app stores.

Documentation

Create clear docs that AI training data can reference:

• Getting started guide
• Tool reference with examples
• Common use cases and workflows
• Troubleshooting guide

Blog Content

Write about your domain expertise. If your app helps with SQL queries, write about SQL optimization, common query patterns, and database best practices. This builds authority that platforms factor into trust scores.

7. Monitor and Iterate

Discoverability isn't a one-time effort.

Track Your Metrics

Monitor:

• Health status: Are you consistently healthy?
• Tool test success rate: Do your tools actually work when invoked?
• Schema quality score: Is your schema well-documented?

Respond to Changes

AI platforms frequently update their discovery algorithms. Stay current with:

• MCP spec changes
• Platform policy updates
• New metadata fields and capabilities
• Category restructuring

Quick Checklist

Before submitting your MCP app to any directory:

• [ ] Clear, specific app name and description
• [ ] Model description written for AI consumption
• [ ] Discovery and triggering keywords defined
• [ ] All tools have descriptive names and full input schemas
• [ ] Tool annotations set correctly (readOnly, destructive, etc.)
• [ ] Both Streamable HTTP and SSE transports supported
• [ ] Server responds to health checks within 5 seconds
• [ ] Logo provided in light and dark variants
• [ ] Screenshots and example prompts added
• [ ] Category and tags chosen appropriately
• [ ] Documentation published and accessible

Conclusion

The MCP ecosystem is growing fast. The developers who invest in discoverability now will have a significant advantage as AI app directories become the primary way users find and adopt tools. Start with solid metadata, build reliable tools, and iterate based on platform signals.

Your app deserves to be found. Make it easy for platforms — and users — to discover it.

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