← All posts
October 13, 2025

How to Get More Usage on Your MCP Server: 5 Proven Strategies

You've built an MCP server. Now what? Learn the exact strategies to increase adoption, reach more developers, and track what's actually working.

How to Get More Usage on Your MCP Server: 5 Proven Strategies

You’ve built an MCP server. Maybe it’s a Stripe integration, a database connector, or something custom. You tested it locally, and it works great.

But here’s the thing: building it is only half the battle.

The Model Context Protocol ecosystem is exploding right now. OpenAI adopted MCP in March 2025. Google announced support in April. Hundreds of servers are launching every month. If you’re not working on discoverability, your server is basically invisible - no matter how good it is.

I’ve looked at successful MCP launches and honestly, the servers that get traction aren’t always the most sophisticated. They’re just the ones that show up where developers are looking.

Here are five strategies that actually work. Not theory, just tactics you can start this week.

1. Publish on All MCP Directories

Look, this sounds obvious, but most people stop after listing in one place. That’s a mistake.

The Core Directories

Start with the official channels:

GitHub - The official MCP servers repo is non-negotiable. Getting listed here is your baseline for credibility. Also make sure your own repo README is clear - one-sentence description, install command, and example above the fold.

Package Registries - Publish to npm (TypeScript/JavaScript) or PyPI (Python). Let developers run npx your-server-name or uvx your-server-name without manual setup.

MCP Directories - These are newer but growing fast:

Optimize Your Listings

Every listing is a mini landing page. Here’s what converts:

Write for humans. Your description should answer: “What can I do with this that I couldn’t before?”

Bad: “MCP server for GitHub API integration” Good: “Ask Claude to create issues, analyze commits, and review PRs from your chat”

Keep install simple. Three lines max:

npm install -g your-mcp-server
claude mcp add your-mcp-server
# Done

Add a demo. A 5-second GIF showing your server in action beats a wall of text.

The Multiplier Effect

Here’s what most people miss: each directory compounds your discovery. When someone finds you on GitHub, they share it. Someone else sees it on mcpso and blogs about it. That post gets indexed, and suddenly you’re in web searches.

One developer saw 300% more usage after listing everywhere over two weeks. Same server, just better distribution.

2. Optimize for LLM Discovery (GEO)

SEO is… well, it’s changing fast. Research says LLM traffic might overtake Google search by late 2027. For MCP servers, this means optimizing for how AI agents discover tools, not just humans.

What Is GEO?

Generative Engine Optimization is about making your stuff understandable to LLMs. When someone asks Claude “what MCP server should I use for email?”, the model doesn’t search Google. It reasons through descriptions and metadata.

Your job: make sure your description makes sense in that context.

GEO Tactics

Use clear descriptions with real examples:

Bad:

{
  "name": "awesome-email-mcp",
  "description": "Revolutionary email solution"
}

Good:

{
  "name": "email-automation-mcp",
  "description": "Send emails, schedule campaigns, analyze open rates. Works with Mailchimp, SendGrid, SMTP. Use cases: automated follow-ups, bulk sending, A/B testing."
}

Structure your README with bullets and headings:

## What This Does
- Creates transactional emails
- Schedules campaigns
- Tracks opens and clicks

## Common Use Cases
- User onboarding
- Invoice delivery
- Newsletter automation

Name tools clearly. Use verbs: send_email not email_handler. Add docstrings explaining what each tool does and when to use it.

Add metadata to package.json or pyproject.toml:

{
  "keywords": ["mcp", "email", "automation", "mailchimp", "campaigns"]
}

The Numbers

Research shows GEO strategies improve visibility by 22% on position-adjusted word count. For us, that means: include real numbers in your README.

“Used by 500+ developers” beats “popular server”. “Setup in 5 minutes vs 2 hours” is memorable.

3. Create a Claude Code Plugin

This is the fastest way to reach active Claude users. Claude Code recently added plugin support in 2025, and it makes installation one-click instead of multi-step.

Why This Matters

Without a plugin:

1. Find GitHub repo
2. Clone or npm install
3. Run claude mcp add
4. Configure auth
5. Restart
6. Test

With a plugin:

1. Enable in Claude Code
2. Done

That friction difference is huge. Convenience compounds adoption.

How to Build One

  1. Package your server as a Desktop Extension (.mcpb file) with all dependencies
  2. Set up OAuth if needed - Claude Code has native support for this
  3. Configure scope - local, project, or user level
  4. Publish to the plugin directory with a clear description

One developer wrapped their API server in a plugin and saw adoption go from 3 people to 47 in a week. That’s 15x just from removing friction.

4. Build a ChatGPT App

Claude isn’t the only option. ChatGPT has massive reach, and many users don’t even know MCP exists.

ChatGPT MCP Support

As of October 2025, ChatGPT supports MCP through Agent Workflows and the Apps SDK. The Apps SDK launched in October and lets you build apps that use MCP servers.

Developer Mode - Full MCP client support for Pro/Team/Enterprise users

Custom Connectors - Connect to third-party apps and internal sources via MCP

How to Integrate

Your MCP server needs HTTP access (ChatGPT connects remotely, not locally like Claude). Test in both chat mode and deep research mode.

Build a custom GPT that wraps your functionality:

  • Name: “GitHub Assistant Pro”
  • Description: “Create issues, review PRs through conversation”
  • Actions: Connected to your MCP endpoints

The Discovery Advantage

ChatGPT’s GPT Store is a discovery engine. When someone searches “GitHub automation”, your app shows up even if they’ve never heard of MCP.

The smart move: offer both. MCP server for power users, ChatGPT GPT for convenience. Same features, two channels.

5. Track Analytics and Double Down

You can’t improve what you don’t measure, right? Most devs launch, see some downloads, and assume it’s working. But “working” and “growing strategically” are different.

What to Track

Discovery - Which directory drives installs? GitHub vs npm vs PulseMCP?

Usage - Which tools get called most? Average session length? Error rates?

Performance - Response times, token usage, auth failures

Retention - Do people come back after first use? Where’s the drop-off?

User Identification - What users use your MCP server? Are they enterprise? Are they paying? Are they just indie hackers?

How to Track

Honestly, the easiest way is to just use Agnost AI. Add analytics with one line of code and start tracking data in 2 minutes.

MCP Analytics Dashboard

We have SDKs for Python, Go, and TypeScript. Check out docs.agnost.ai for integration guides.

Want help setting it up? Get on a call at call.agnost.ai

Act on the Data

Once you see patterns, act. If 60% of users come from the official MCP repo, invest more there. Add examples, video demos, engage with issues.

If your search_repos tool has 20% errors from rate limits, add caching and retry logic.

One team found 70% of users came from ChatGPT recommendations. They optimized with GEO tactics and doubled that traffic in a month.

Small changes, compounded by data, create big results.

The Reality Check

Look, not every server needs aggressive growth. If you built something internal, one listing might be enough.

But if you’re building in public and want your server to become a standard tool, you need distribution. The best servers aren’t just well-coded - they’re well-marketed.

These five strategies are about being systematically discoverable where developers and AI agents look.

Your Action Plan

Day 1: Directory Blitz - List on GitHub, npm/PyPI, mcpso, PulseMCP, and Smithery.

Day 2: GEO Audit - Rewrite your README with bullet points, use cases, and structured metadata.

Day 3: Plugin - Start wrapping your server as a Claude Code plugin.

Day 4: ChatGPT - Set up HTTP access and test in ChatGPT’s Apps SDK.

Day 5: Analytics - Add tracking. Start with basics: usage, errors, latency.

Days 6-7: Iterate - Watch the data and adjust.

The Bottom Line

Building an MCP server is great. Getting people to use it is the hard part.

The servers that win show up in searches, work across platforms, and remove barriers to adoption.

Publish everywhere. Optimize for AI. Reduce friction with plugins. Track what works. Repeat.

If you want help tracking where adoption is leaking, we built Agnost AI to give you instant visibility. One line of code, real-time insights.

Now go make your server impossible to ignore.

Key Takeaway: MCP adoption isn’t luck - it’s about showing up where developers look, removing friction everywhere, and doubling down on what actually drives usage.