The first quarterly MCP reliability report. Three months of data, 2.17M+ health checks, and a clear picture of where the ecosystem stands.
Published April 1, 2026 • Data period: January – March 2026
In Q1 2026, MCPulse performed 2.17M health checks across 615 MCP servers. The ecosystem average reliability score is 54.3% — indicating significant room for improvement.
Only 33 servers (5.4%) achieved "Excellent" status (90%+ reliability). Meanwhile, 200 servers (32.5%) scored below 50%, classified as "Poor." The largest cohort — 304 servers (49.4%) — sits in the "Fair" tier, suggesting most MCP servers work but aren't production-grade yet.
Health check volume grew ~4.9x from February to March as MCPulse expanded monitoring coverage. This is the first quarter of operation, establishing the baseline for future comparisons.
How the ecosystem performed month-over-month throughout Q1.
Health check volume increased ~4.9x from February to March as monitoring coverage expanded. The success rate stayed roughly flat (17.0% → 15.0%), confirming the low ecosystem reliability isn't a measurement artifact — it's structural. Most MCP servers simply aren't built for uptime yet.
How all 615 servers stack up across reliability tiers.
The takeaway: Only 18.1% of MCP servers are "Good" or better. Over half sit in the "Fair" tier — functional but unreliable for production workloads. If you're building on MCP, you need to be selective about which servers you depend on.
The servers that delivered consistent reliability throughout Q1 2026.
These servers experienced persistent issues throughout Q1. Maintainers: claim your server to get alerts and improve.
How different categories of MCP servers compare in Q1 reliability.
At 54.3% average reliability, the MCP ecosystem is not production-ready for most use cases. Only 5.4% of servers meet the 90%+ bar that developers expect from infrastructure. This is Q1 — the baseline. Every future quarter will be measured against these numbers.
The 33 servers in the Excellent tier averaged 94.8% reliability — proving that high MCP reliability is achievable. These servers tend to have well-maintained GitHub repos, responsive maintainers, and proper health check endpoints.
MCPulse went from 368.0K checks in February to 1.80M in March. This expansion means the March data is significantly more representative. Q2 data will benefit from a full quarter at high-volume monitoring.
49.4% of servers land in the Fair tier (50-69% reliability). These servers respond to health checks but fail often enough to be unreliable for automated workflows. If you're building AI agents that depend on MCP servers, "Fair" isn't good enough.
99.99% of successful health checks completed in under 100ms. The problem isn't speed — it's availability. Servers either respond instantly or don't respond at all. There's almost no "slow" middle ground.
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This report is based on real production data from MCPulse's monitoring infrastructure. Every metric comes from actual health checks performed against live MCP servers — no simulations or extrapolations.
reliability_score =
uptime_percentage × 0.40
+ response_time_score × 0.30
+ error_rate_score × 0.20
+ consistency_score × 0.10
All data is accessible via our public server directory and API. Individual server profiles show full 30-day history with heatmaps and trend data.
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