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Bar chart showing 54% of 39,762 MCP servers with zero community adoption, illustrating low engagement in the ecosystem
Open SourceScore: 90

MCP Server Report: 54% of 39,762 Servers Have Zero Community Adoption —

54% of 39,762 MCP servers are invisible to AI agents due to zero community adoption. Use Agent Tool Intelligence's new grading model to boost your server's discoverability.

·1d ago·3 min read··22 views·AI-Generated·Report error
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Source: dev.tovia devto_mcp, devto_claudecode, simon_willison, hn_claude_codeWidely Reported
How do I make my MCP server discoverable to AI agents?

54% of MCP servers (21,464 out of 39,762) have Grade C quality but zero community adoption. To make your server discoverable to AI agents, get 10+ GitHub stars and maintain recent activity. Check your grade at agent-tool-intel-production.up.railway.app.

TL;DR

54% of MCP servers have solid code but zero community adoption, making them invisible to AI agents. Get 10+ stars and stay active to rank higher.

Key Takeaways

  • 54% of 39,762 MCP servers are invisible to AI agents due to zero community adoption.
  • Use Agent Tool Intelligence's new grading model to boost your server's discoverability.

What Changed — The New Grading Model for MCP Servers

The MCP ecosystem just crossed 39,762 indexed servers, and Agent Tool Intelligence released its June 2026 report with a completely rebuilt scoring engine. The old system scored 85.7% of tools as Grade B — useless for differentiation. Now they use a three-dimensional additive model: Quality Score + Community Bonus + Trust Bonus.

Here's the breakdown that matters to you:

  • B+ (1,123 servers, 2.8%): Very good — close to elite
  • B (7,187 servers, 18.1%): Good — solid quality + some community
  • C+ (5,477 servers, 13.8%): OK — decent quality
  • C (21,464 servers, 54.0%): Average — good foundation, no community signal
  • D (4,351 servers, 10.9%): Needs work
  • F (160 servers, 0.4%): Critical

What It Means For You — The Discoverability Problem

If you've built an MCP server and nobody's using it, you're in the 54%. Your code could be perfect, but AI agents don't know it exists. The report's key insight: "54% of MCP tools have solid code quality but zero community adoption. They're invisible to AI agents."

This is a huge problem because Claude Code, which uses the Model Context Protocol extensively (58 sources confirm this connection), relies on discoverable servers to extend its capabilities. If your server isn't on the radar, it's like having a library with no catalog.

Try It Now — How to Boost Your Server's Grade

EP163: 12 MCP Servers You Can Use in 2025

The path from C to B is clear: get 10+ GitHub stars + stay active. Here's your action plan:

  1. Check your current grade: Go to agent-tool-intelligence.com and search for your server.
  2. Get 10+ GitHub stars: Share your server on r/ClaudeCode, Hacker News, or Dev.to. A single post can get you there.
  3. Push within 30 days: The report shows 100% of indexed servers are active. If yours isn't, it drops off.
  4. Add documentation and examples: The Quality Score component rewards clear READMEs and usage examples.

For your Claude Code workflow, you can also use the claude mcp add command to manually connect to any server, but discoverability matters when you're searching for new tools.

Why This Matters for Claude Code Users

The MCP ecosystem is the backbone of Claude Code's extensibility. As we've reported, Claude Code uses MCP extensively, and GitHub itself now uses the protocol. The recent launch of Spec-Kit (June 7, 2026) shows how MCP is becoming standard infrastructure.

If you're building MCP servers for your team or company, this grading system is your SEO. A B+ rating means your server gets surfaced when AI agents search for tools. A C rating means you're invisible.

Quick Tips

  • For server builders: Focus on community signals. Stars and activity matter more than perfect code.
  • For users: Use the grading tool to find high-quality servers before adding them to Claude Code.
  • For both: The methodology is open source at github.com/agent-tool-intel/agent-tool-intel — you can even contribute to the scoring model.

Source: dev.to

Source: gentic.news · · author= · citation.json

AI-assisted reporting. Generated by gentic.news from multiple verified sources, fact-checked against the Living Graph of 4,300+ entities. Edited by Ala SMITH.

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AI Analysis

Claude Code users should immediately check their MCP server's grade at the Agent Tool Intelligence portal. If your server is Grade C or below, stop optimizing code and start building community. Push a new update, share your server on developer forums, and aim for 10+ stars. This is the single highest-leverage action for making your server discoverable to AI agents. For users consuming MCP servers, use the grading system as a filter. Only add servers rated B+ or B to your Claude Code configuration. This reduces noise and ensures you're connecting to tools that have proven quality and community validation. You can add a server with `claude mcp add github.com/username/server-name` but verify its grade first. Finally, watch for the next report. The ecosystem grew to 39,762 servers — that's massive. The old grading system was useless; the new one is actionable. Bookmark the portal and check it monthly to stay ahead.
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