Correctover MCP Server
OfficialThe Correctover MCP Server acts as an intelligent intermediary that validates LLM responses in real-time across six dimensions and automatically self-heals through retries or failover to ensure reliable AI outputs.
Core Validation (6 Dimensions): Structure (JSON/YAML well-formedness, required fields), Schema (type correctness, enum compliance), Latency (SLA thresholds), Cost (token usage/budget), Identity (model/provider match), and Integrity (content tampering, hash verification).
Tools:
chat— Send messages to LLMs with automatic 6-dimension validation and failover. Supports specifying provider, model, temperature, max tokens, and system prompts; returns a detailed validation report.health— Check availability and status of all configured LLM providers before use.providers— View supported providers (OpenAI, Anthropic, DeepSeek, Groq, Alibaba Qwen, Zhipu/GLM, SiliconFlow, Together, Moonshot/Kimi, etc.) with default models, base URLs, and configuration status.stats— Review session metrics: total API calls, validation pass rate, failover count, active providers, and server version.validation_history— Paginate through up to 500 recent validation records (newest first), each showing provider, model, latency, pass/fail status, score, and failure reasons.
Prompts: Pre-built prompts for verifying AI output (verify-output), comparing providers (compare-providers), and running reliability audits (reliability-audit).
BYOK (Bring Your Own Key): API keys stay on your machine — no proxying or data collection.
Provides integration with OpenAI's API for chat completion with automatic verification and self-healing.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Correctover MCP Serververify the AI output for correctness and completeness"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Correctover MCP Server
The first MCP server that verifies AI outputs in real-time.
Correctover sits between your AI tool (Cursor, Claude Desktop, Windsurf) and LLM providers, validating every response across 6 dimensions with automatic self-healing failover.
What It Does
When an LLM returns a response, Correctover validates it in real-time:
Dimension | What It Checks |
Structure | JSON/YAML well-formedness, required fields present |
Schema | Type correctness, enum compliance, nested object validation |
Latency | Response time within SLA thresholds |
Cost | Token usage and cost within budget limits |
Identity | Output matches expected model/provider identity |
Integrity | No content tampering, hash verification |
If any dimension fails, the engine auto-retries or fails over to another provider — then validates again. Every response that reaches your application has passed all 6 checks.
Related MCP server: Kluster.ai Verify MCP
Quick Start
Install via npm
npm install -g correctover-mcp-serverConfigure your AI tool
Add to your mcp.json (Cursor, Claude Desktop, Windsurf):
{
"mcpServers": {
"correctover": {
"command": "correctover-mcp-server",
"env": {
"OPENAI_API_KEY": "sk-...",
"ANTHROPIC_API_KEY": "sk-ant-...",
"DEEPSEEK_API_KEY": "sk-..."
}
}
}
}That's it. BYOK (Bring Your Own Key) — your keys stay on your machine. No proxy, no data collection.
Supported Providers
Provider | Models | Env Variable |
OpenAI | GPT-4o, GPT-4o-mini, o1 |
|
Anthropic | Claude 3.5 Sonnet, Haiku, Opus |
|
DeepSeek | DeepSeek-V3, DeepSeek-R1 |
|
Moonshot/Kimi | Moonshot-v1 |
|
Alibaba Qwen | Qwen-Max, Qwen-Plus |
|
Zhipu/GLM | GLM-4 |
|
SiliconFlow | Multiple open models |
|
Groq | Llama, Mixtral |
|
Together | Llama, Mistral |
|
Set at least one API key. Correctover auto-detects configured providers.
Tools
chat — Verified Chat
Send a message to any LLM with automatic 6-dimension validation. Routes through the best provider, validates output, self-heals on failure.
{
"messages": [{"role": "user", "content": "Generate a JSON config"}],
"model": "auto"
}Response includes:
The LLM output text
A validation report showing which dimensions passed/failed
Failover count (if any)
health — Health Check
Check which providers are configured and ready before starting work.
providers — Provider Details
See detailed configuration for all supported providers (base URLs, models, status).
stats — Session Statistics
Review session metrics: total calls, validation pass rate, failover count, active providers, server version.
validation_history — Validation Records
Query recent validation results with pagination (ring buffer, 500 records). Each record includes provider, model, latency, pass/fail status, score, and failure reasons.
Prompts
Prompt | Description |
| Verify AI-generated content for correctness across 6 dimensions |
| Compare responses from multiple providers on the same prompt |
| Run a comprehensive reliability audit on your provider setup |
How It Works
Your AI Tool (Cursor/Claude Desktop)
│
▼
┌─────────────────────────┐
│ Correctover MCP │
│ ┌───────────────────┐ │
│ │ 6-Dim Validator │ │
│ │ ┌─ Structure │ │
│ │ ├─ Schema │ │
│ │ ├─ Latency │ │
│ │ ├─ Cost │ │
│ │ ├─ Identity │ │
│ │ └─ Integrity │ │
│ └───────────────────┘ │
│ │ │
│ ┌──────▼──────┐ │
│ │ Failover │ │
│ │ Engine │ │
│ └──────┬──────┘ │
└──────────┼──────────────┘
│
┌──────┼──────┬────────┐
▼ ▼ ▼ ▼
OpenAI Anthropic DeepSeek Qwen ...Route → Select best provider by priority and health
Call → Send request to LLM provider
Validate → Run 6-dimension checks on response
Pass? → If yes, return to your AI tool
Fail? → Auto-retry or failover to next provider → Go to step 2
Failover ≠ Correctover
Simple failover just switches providers when one goes down. Correctover switches and verifies the output is correct before delivering it. Every response passes through 6-dimension validation — if it fails, the engine auto-retries or fails over, then re-validates.
Configuration
Custom Base URLs
For API proxies or compatible endpoints:
{
"env": {
"OPENAI_API_KEY": "your-key",
"OPENAI_BASE_URL": "https://your-proxy.example.com/v1"
}
}Environment Variables
Variable | Required | Description |
| No* | OpenAI API key |
| No* | Anthropic API key |
| No* | DeepSeek API key |
| No* | Moonshot/Kimi API key |
| No* | Alibaba DashScope (Qwen) |
| No* | Zhipu/GLM API key |
| No* | SiliconFlow API key |
| No* | Groq API key |
| No* | Together AI API key |
*At least one API key is required.
System Requirements
Node.js ≥ 18.0.0
Platform: Linux (amd64/arm64), macOS (amd64/arm64), Windows (amd64)
The npm installer automatically downloads the correct binary for your platform
Commercial Support
For teams building production AI agents:
Enterprise support: Priority bug fixes, SLA guarantees, dedicated support
Custom integration: We'll integrate Correctover into your agent stack
Security audits: We've audited 50+ MCP implementations
On-premise deployment: Run Correctover in your infrastructure
Contact: wangguigui@correctover.com
Links
Protocol Spec: Correctover/standards (CC BY 4.0)
npm Package: correctover-mcp-server
Glama: correctover/mcp-server
Website: correctover.com
Issues: GitHub Issues
License
Apache 2.0 © Correctover
Maintenance
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