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io.github.mdfifty50-boop/qc-validator

Official registry AI and agents

Output quality control and validation for AI agents

Source code Documentation

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

NPM package qc-validator-mcp
Claude Code 
claude mcp add qc-validator -- npx -y qc-validator-mcp@0.1.3
JSON configuration (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "qc-validator": {
            "command": "npx",
            "args": [
                "-y",
                "qc-validator-mcp@0.1.3"
            ]
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. qc-validator-mcp
  2. Install
  3. Tools
  4. Resource
  5. Architecture
  6. License

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

Frequently asked questions

What is io.github.mdfifty50-boop/qc-validator?

Output quality control and validation for AI agents

How do I install io.github.mdfifty50-boop/qc-validator?

It runs on your machine. In Claude Code: claude mcp add qc-validator -- npx -y qc-validator-mcp@0.1.3. For other clients, paste the JSON configuration from this page into their MCP settings.

Does io.github.mdfifty50-boop/qc-validator need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is io.github.mdfifty50-boop/qc-validator open source?

Its code is public on GitHub, but the repository does not declare a standard license.

Who maintains io.github.mdfifty50-boop/qc-validator?

It is published by mdfifty50-boop. AI.tn lists it but does not maintain or endorse it.

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