Stop AI Hallucinations in Research Using MCP.
Claims sourced, hallucinations flagged, attack plan verified , build competitive strategy that survives fact-checking
Works with every AI agent you already use
…and any MCP-compatible client
Waiting for input…
Gemini How It Works
Your AI agent receives a competitive analysis request: 'Analyze our main competitor for the CI/CD market.' Phase 1: the agent runs `validate_competitive_intel`.
It forces verifiable sources for every claim , not 'they have approximately $50M revenue' but 'Crunchbase Series C: $38M raised (2024-03-15), estimated ARR based on 2,400 customers at average contract value $18K (from their pricing page, verified 2024-06-01) = $43.2M.' It quantifies weaknesses with observable evidence , not 'poor UX' but 'G2 reviews #14523, #14601: 14-step onboarding process.
Our testing (2024-06-01): first deploy takes 23 minutes vs. our 4 minutes for identical repository.' It builds a resource-constrained attack plan , WHO: 1 developer + 1 content marketer.
WHEN: 2 weeks. COST: $0 (organic SEO play). WHAT: 'Migrate from [Competitor]' landing page targeting long-tail keywords. Kill criterion: if the page does not rank top 20 within 60 days, pivot to paid acquisition.
Phase 2: the agent runs `validate_hallucination_grounding` on the entire competitive report. Source Citation: flags any remaining 'Studies show...' or 'Industry reports suggest...' without DOI or URL.
Confidence Calibration: maps each claim to evidence quality , pricing page (high confidence) vs. a single Reddit comment (low confidence).
Fact vs. Opinion: catches statements like 'Their platform is clearly inferior' and relabels as OPINION. Internal Consistency: cross-references all numbers across the report , if page 2 says '2,400 customers' and page 5 says '3,000+ enterprises,' the contradiction is flagged.
Knowledge Boundaries: forces the model to state its training cutoff and flag any market data that may be stale. The final deliverable: a competitive brief where every number has a link, every opinion is labeled, and every attack plan has a budget and a kill date.
MCP Server Orchestration: 2 MCP Servers, one intelligent agent
Connect Competitive Intelligence Prover and Hallucination Detector Prover MCP servers so your AI agent builds a competitor analysis where every claim is fact-checked, every number has a verifiable source, and every attack plan is feasible with your actual resources. Product and strategy teams get a two-layer validation: first, the agent validates competitive claims against verifiable sources, quantifies weaknesses with observable evidence, and builds resource-constrained attack plans. Then, it runs the entire analysis through hallucination detection , flagging fabricated statistics, separating opinion from fact, catching internal contradictions, and forcing confidence calibration on every claim. The result is competitive intelligence that survives board-room scrutiny because every data point has a citation trail.
Competitive Intelligence Prover
triggerValidates competitor claims against verifiable sources, quantifies weaknesses, and builds feasible attack plans
validate_competitive_intel Hallucination Detector Prover
actionAudits the competitive analysis for fabricated claims, opinion-as-fact mixing, and internal contradictions
validate_hallucination_grounding Run This Automation Today
Connect Claude, ChatGPT, Cursor, or any AI agent to the Vinkius catalog and run this automation in minutes.
Build Your Own MCP
Turn any internal API into an MCP server. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Connect & Automate
The 2 servers this recipe uses are ready in the catalog. Connect them once, paste a prompt, and your AI runs the full workflow.
- Competitive Intelligence Prover & Hallucination Detector Prover ready in the catalog right now
- Add more from 4,700+ servers whenever you need
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers and recipes added every week
Superpowers you didn't know your AI had
The Vinkius catalog gives your agent access to 4,700+ MCP servers and the intelligence to combine them. Imagine never logging into another dashboard. Your AI handles the work across every tool, in one conversation. That's what this infrastructure was built for.
Cross-Platform Intelligence
Your agent doesn't just connect to tools. It understands the relationships between them. Data flows where it needs to go, automatically, with full context preserved across every platform.
Contextual Reasoning
Every decision your agent makes considers the full picture. It reads CRM data, checks calendars, reviews conversation history, and acts on everything at once. Not step by step. All at once.
Productivity at Scale
What used to take 45 minutes across five different dashboards now takes one sentence. Your agent runs the entire workflow end to end while you focus on decisions that actually matter.
Zero-Config Reliability
No API keys to paste. No webhooks to configure. No YAML to debug. Connect your MCP servers once, and your agent handles the rest. Every time, without intervention.
Made for
exactly this
Your AI agent taps into the entire Vinkius MCP catalog to handle these for you. You describe what you need. It does the rest.
Product managers preparing competitive landscape analyses for board meetings who need every claim backed by a verifiable source with zero fabricated statistics
Strategy directors building market entry plans against established competitors who need resource-constrained attack plans with measurable kill criteria
Marketing teams creating competitive comparison pages who need fact-checked claims that survive legal review and competitor scrutiny
Startup founders preparing investor decks who need competitive positioning that acknowledges both strengths and vulnerabilities with verified market data
Frequently Asked Questions About This MCP Server Orchestration
Which MCP servers do I need for this workflow?
Two: Competitive Intelligence Prover and Hallucination Detector Prover. Connect both to your AI client.
Does this work with Claude Desktop, Cursor or Windsurf?
Yes. Any AI client that supports the Model Context Protocol works , Claude Desktop, Cursor, Windsurf, Cline and others.
Why do I need both Provers? Is the Competitive Intelligence Prover not enough?
The Competitive Intelligence Prover validates strategic soundness , are the claims sourced? Is the attack plan feasible? But it does not detect AI hallucination patterns. The Hallucination Detector catches fabricated statistics, opinion-as-fact mixing, and internal contradictions that competitive analysis alone misses. Together, they produce intelligence that is both strategically sound and factually grounded.
What counts as a verifiable source?
Seven categories: their website (pricing, features, changelogs), review platforms (G2, Capterra with review IDs), public financials (Crunchbase, SEC filings), user complaints (Reddit threads, GitHub issues), job postings, your own hands-on testing with dates, and App Store reviews. Minimum 3 independent sources to triangulate any major claim.
Can this workflow be used for investor presentations?
It was designed for exactly this. Every number has a citation trail, every opinion is labeled, and every attack plan has a budget and kill criterion. This is the format that survives due diligence scrutiny.
How does the Hallucination Detector handle estimated numbers?
It flags derived calculations as MEDIUM confidence and requires transparency. For example, estimating revenue from customer count times average contract value is flagged as a calculation, not a confirmed figure. The estimate stands, but with an explicit confidence qualifier.
MCP servers used in this workflow
Competitive Intelligence Prover
Competitive Intelligence Prover. This tool forces your AI agent to conduct fact-grounded competitive analysis. It rejects vague opinions and fabricated data, requiring every claim to cite a verifiable source, measuring weaknesses, and defining actionable, resource-limited attack plans. It validates strategy against measurable metrics and internal gaps.
Hallucination Detector Prover
Hallucination Detector Prover forces LLMs to prove every fact they state. This tool demands verifiable sources (DOI/URL), quantifies confidence per claim against evidence quality, separates subjective opinion from hard facts, and checks for internal contradictions across the entire text output.