The first contract-validation MCP server on the Official Registry — because failover switches, but Correctover verifies.
What Just Happened
Correctover MCP Server (v1.0.3) is now live on the Official MCP Registry — the same registry VS Code 1.102+ uses to discover MCP tools.
This means: any developer using Cursor, Claude Desktop, VS Code, or Windsurf can type correctover in their MCP settings and instantly get contract-validation capabilities inside their AI assistant.
No gateway. No proxy. No Docker. No K8s. Just npx -y correctover-mcp-server.
Why This Matters
Most developers using LLM APIs rely on failover — switching providers when one goes down. But failover only checks one thing: "did Provider B respond?"
Here's what failover never checks:
- Model substitution: You request GPT-4o, silently receive GPT-4o-mini. You pay 4o tokens, get mini quality.
- Schema drift: Your structured output suddenly drops a required field. Downstream pipeline crashes.
- Cost overruns: Token count doesn't match what the requested model should produce.
- Semantic quality: The output "looks OK" but doesn't actually satisfy your prompt intent.
Failover answers: did it respond?
Correctover answers: is the response correct?
That's the gap. And now your AI coding assistant can help you close it.
How It Works: Inside Your IDE
Install the MCP server in your IDE config:
{
"mcpServers": {
"correctover": {
"command": "npx",
"args": ["-y", "correctover-mcp-server"],
"env": {
"DEEPSEEK_API_KEY": "your-key",
"MOONSHOT_API_KEY": "your-key",
"DASHSCOPE_API_KEY": "your-key"
}
}
}
}
Once connected, your AI assistant can:
- Validate LLM responses — Ask "is this GPT-4o response contractually correct?" and get a 6-dimension analysis (structure, schema, latency, cost, identity, integrity)
- Test failover paths — Ask "simulate an OpenAI timeout and verify the DeepSeek fallback response" — get real-time contract validation on the switched provider
- Detect silent model swaps — Ask "check if my recent API calls received the correct model" — get identity verification results
- Monitor API health — Ask "what's the health score of my configured providers?" — get real-time status
All inside your coding workflow. No separate dashboard needed.
6-Dimension Contract Validation
The CANON engine validates every response across 6 dimensions in 22μs P50:
| Dimension | What It Checks | Example Failure |
|---|---|---|
| Structure | Response format matches schema | JSON missing choices array |
| Schema | Required fields + correct types |
action_items field is null |
| Latency | Response time within SLA | 15s response from normally 1s provider |
| Cost | Token usage matches model range | 4o pricing but mini token output |
| Identity | Model matches requested model | Requested 4o, received 4o-mini |
| Integrity | Output meets quality threshold | Summary misses critical clauses |
The overhead is <0.01% of a typical LLM call (200-2000ms). You literally cannot measure the difference.
BYOK — Zero Markup, Zero Token Resale
Correctover uses your own API keys. Direct connect to providers:
- DeepSeek (via Anthropic-compatible endpoint)
- Moonshot / Kimi
- Alibaba DashScope (Qwen models)
- OpenAI (coming soon)
- Anthropic (coming soon)
No middleman. No token resale. No markup. Your data stays in your process.
Installation Options
VS Code 1.102+: Search "correctover" in MCP Extensions → Install
Cursor / Claude Desktop / Windsurf: Add to your mcp.json:
{
"mcpServers": {
"correctover": {
"command": "npx",
"args": ["-y", "correctover-mcp-server"],
"env": {
"DEEPSEEK_API_KEY": "sk-xxx",
"MOONSHOT_API_KEY": "sk-xxx",
"DASHSCOPE_API_KEY": "sk-xxx"
}
}
}
}
Smithery: Deploy with one click — scored 82/100 on quality assessment.
npm: npm install correctover-mcp-server
What's Different from Other MCP Servers
| Feature | Typical LLM MCP | Correctover MCP |
|---|---|---|
| Routes requests to LLMs | ✓ | ✓ |
| Validates response contracts | ✗ | ✓ |
| Detects silent model swaps | ✗ | ✓ |
| Catches schema drift | ✗ | ✓ |
| Prevents cost overruns | ✗ | ✓ |
| Self-healing (87 rules) | ✗ | ✓ |
| BYOK zero markup | ✗ | ✓ |
Other MCP servers help you call LLMs. Correctover helps you trust the responses.
The Numbers
| Metric | Value |
|---|---|
| Contract validation P50 | 22μs |
| Contract validation P99 | 99μs |
| L3 Failover E2E | 949ms |
| Self-healing rules | 87 |
| MCP Server version | 1.0.3 |
| Package size | <500KB |
| Dependencies | Minimal |
Why MCP Matters for LLM Reliability
MCP (Model Context Protocol) is becoming the standard way AI assistants interact with external tools. By making contract validation available as an MCP tool, Correctover bridges two worlds:
- Your AI coding assistant — which helps you write code that calls LLM APIs
- Your LLM API reliability — which ensures those calls produce correct results
Before: you write LLM code → hope it works → manually check dashboards
After: you write LLM code → assistant validates contracts in real-time → catches silent failures before they cascade
Try It Now
# Quick test without IDE integration
npx correctover-mcp-server
Or add to your IDE and ask your assistant:
"Use correctover to validate whether my last DeepSeek API call returned the correct model and schema."
Because failover switches. Correctover verifies.
Apache-2.0 WITH commercial-restriction. Free for dev/non-commercial use.
© 2026 Guigui Wang. All rights reserved.