Qc Validator
A validation layer that sits between your AI agent and its output. Exposes six tools: validate_output scores responses against length limits and keyword requirements, check_hallucination_risk flags unsupported claims by checking sentence grounding against source text, and check_scope_compliance enforces topic boundaries and required sections. The last three tools (log_validation, get_failure_patterns, generate_quality_report) track validation history per agent so you can spot recurring failure modes. Everything runs in memory with no external dependencies. Reach for this when you need programmatic guardrails on agent responses, especially if you're building multi-agent systems where output quality varies and you want telemetry on which agents drift off scope or hallucinate most often.
- tools
- 6
- transport
- STDIO
- last updated
- Apr 24, 2026
Tools
6 toolsPublic tool metadata for what this MCP can expose to an agent.
validate_outputScore agent output against configurable criteria: length limits, required keywords, forbidden patterns, and factual claim density.
Score agent output against configurable criteria: length limits, required keywords, forbidden patterns, and factual claim density.
No parameter schema in public metadata yet.
check_hallucination_riskEstimate hallucination likelihood. With source text, checks sentence-level grounding. Without source, flags outputs dense with specific numbers, dates, and URLs.
Estimate hallucination likelihood. With source text, checks sentence-level grounding. Without source, flags outputs dense with specific numbers, dates, and URLs.
No parameter schema in public metadata yet.
check_scope_complianceValidate output against a scope contract — allowed/forbidden topics, word limits, required sections.
Validate output against a scope contract — allowed/forbidden topics, word limits, required sections.
No parameter schema in public metadata yet.
log_validationStore validation results for per-agent trending.
Store validation results for per-agent trending.
No parameter schema in public metadata yet.
get_failure_patternsAnalyze common failure modes for a specific agent.
Analyze common failure modes for a specific agent.
No parameter schema in public metadata yet.
generate_quality_reportQuality dashboard across all validated agents — no parameters required.
Quality dashboard across all validated agents — no parameters required.
No parameter schema in public metadata yet.
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qc-validator-mcp
Runtime quality validation for AI agent outputs. Detect hallucinations, enforce scope compliance, and score output quality — all via MCP.
Install
npx qc-validator-mcp
Claude Desktop
{
"mcpServers": {
"qc-validator": {
"command": "npx",
"args": ["qc-validator-mcp"]
}
}
}
Tools
validate_output
Score agent output against configurable criteria: length limits, required keywords, forbidden patterns, and factual claim density.
Params: output, task_description, criteria { max_length, required_keywords[], forbidden_patterns[], factual_claims_count }
Returns: { pass, score, issues[], recommendation }
check_hallucination_risk
Estimate hallucination likelihood. With source text, checks sentence-level grounding. Without source, flags outputs dense with specific numbers, dates, and URLs.
Params: output, source_text (optional), claim_count (default 5)
Returns: { risk_level, unsupported_claims[], confidence, suggestion }
check_scope_compliance
Validate output against a scope contract — allowed/forbidden topics, word limits, required sections.
Details
- Repository
- github.com/mdfifty50-boop/qc-validator-mcp
- Package
qc-validator-mcp- Transport
- STDIO
- Registry
- MCP registry, active