About io.github.mdfifty50-boop/qc-validator
io.github.mdfifty50-boop/qc-validator is an MCP server published by mdfifty50-boop in the Developer Tools category: mCP server for runtime quality validation of AI agent outputs — hallucination detection, scope compl.
Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
claude mcp add io-github-mdfifty50-boop-qc-validator -- npx -y qc-validator-mcpnpx -y qc-validator-mcpThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
Tools (6)
check_hallucination_riskEstimate hallucination likelihood in agent output. If source text is provided, checks grounding. Otherwise flags outputs with high counts of specific numbers, dates, and URLs.
Parameters not published.
check_scope_complianceValidate that agent output stays within a defined scope contract. Checks allowed/forbidden topics, word limits, and required sections.
Parameters not published.
generate_quality_reportGenerate a quality dashboard for all validated agents. Shows per-agent summaries, overall pass rate, worst/best performers, and actionable recommendations.
Parameters not published.
get_failure_patternsAnalyze common failure modes for a specific agent. Returns pass rate, average score, most frequent issue types, and quality trend direction.
Parameters not published.
log_validationStore a validation result for trending and failure pattern analysis. Accumulates per-agent statistics over time.
Parameters not published.
validate_outputScore agent output quality against configurable criteria. Checks length, required keywords, forbidden patterns, claim density, and task relevance.
Parameters not published.
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README
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.
Params: output, scope { allowed_topics[], forbidden_topics[], max_words, required_sections[] }
Returns: { compliant, violations[], scope_utilization_percent }
log_validation
Store validation results for per-agent trending.
Params: agent_id, output_hash, score, pass, issues_count
Returns: { logged, agent_id, total_validations }
get_failure_patterns
Analyze common failure modes for a specific agent.
Params: agent_id
Returns: { total_validations, pass_rate, avg_score, most_common_issues[], trend }
generate_quality_report
Quality dashboard across all validated agents — no parameters required.
Returns: { total_agents, overall_pass_rate, agents[], worst_performers[], best_performers[], recommendations[] }
Resource
qc://dashboard— Quality metrics for all validated agents
Architecture
- Pure Node.js ES modules
- In-memory Maps (no external dependencies)
- stdio transport via @modelcontextprotocol/sdk
- Zero configuration required
License
MIT
README copy captured when this server was indexed; it may lag the repository. The original is authoritative.