MCP server

Klarix Intelligence Engine Official

ai.klarix/intelligence

Checked 26 Oct 2026, 08:29 UTC · Not tested (older connection type)

Cited competitive intelligence: prospect scoring, battlecards, SWOT, and tech-stack teardowns.

Not checkedVerified publisher: klarix.ai15 tools

Website

https://mcp.klarix.ai/sse

At a glance

Type: MCP server
Publisher: klarix.ai (verified by the MCP Registry)
Status: Not checked
Tools: 15
Last checked: 26 Oct 2026, 08:29 UTC

Tools

analyze_head_to_head ~665 tokens
Compare YOUR company against a specific competitor or incumbent you want to displace. Researches both sides on the live public web, then returns asymmetric advantages (where you win structurally), their defensive moats (where to stop arguing), a fixed four-dimension comparison matrix (Pricing, Tech
detect_account_triggers ~510 tokens
Detect recent account inflection points (leadership changes, funding, hiring surges, product updates, regulatory events) within a timeframe.
find_matched_prospects ~1154 tokens
Build a first-pass candidate list from hundreds of thousands of pre-profiled B2B companies using Voyage 4 semantic vector embeddings. Ranks accounts by topical similarity to an ICP description, tech stack, business model, and vertical, then screens the retrieved candidates for buyer-vs-vendor role a
generate_displacement_playbook ~481 tokens
Generate an end-to-end competitive displacement playbook with switching cost mitigations, POC blueprints, and migration timelines.
generate_outreach_sequence ~384 tokens
Write cold outreach that opens on a researched, dated insight about the prospect rather than a pleasantry. Supports a 3-step email sequence, a 3-step LinkedIn sequence, or 6 multivariant openers. Enforces the Klarix voice contract (banned AI words and phrases, punctuation tells, rhythm) and reports
generate_swot_analysis ~693 tokens
Deep multi-source web crawl into a four-quadrant SWOT matrix for a company: internal strengths (moat, proprietary tech, distribution lock) and weaknesses (pricing friction, customer complaints, legacy tech), plus external opportunities (untapped verticals, market vacancies, adjacent expansion) and t
get_buying_committee ~470 tokens
Map the internal buying committee (Economic Buyer, Champion, Technical Evaluator, Procurement) for an account with title patterns, pain points, objections, and multi-threading strategy.
get_company_intelligence ~284 tokens
Synthesize an executive one-pager on a company from live public web sources: snapshot, findings per requested focus area, dated buying signals, deal risks, and stated unknowns. Every claim carries a source URL. Focus areas include pricing, leadership (roles only), recent_events, tech_stack, customer
get_competitor_battlecard ~507 tokens
Build a live sales battlecard for a competitor domain: SWOT from their point of view, the gap between their marketing claims and buyer-reported reality, and concrete landmines with spoken talk tracks. Every claim cites a public source. Optionally aim it at a target vertical, and curate it to your ow
get_deep_research ~478 tokens
Exhaustive intelligence probe on a company across five dimensions: firmographic and corporate evolution (funding, revenue tier, team growth), product and technology teardown (stack, API presence, core capabilities), leadership and organizational signals (executive hires, board composition, departure
get_market_landscape ~308 tokens
Map a competitive landscape for an industry or vertical from live public sources: Tier-1 incumbents against emerging disruptors, category positioning quadrants with the white space in each, published pricing models and price bands, and the narrative themes that dominate zero-click and AI answers — i
score_prospect_fit ~666 tokens
Score a company against your ICP on five weighted axes — Strategic Fit, Tech Alignment, Buyer Persona Readiness, Growth Triggers, and Landmine Risk — each 1-10, with a weighted overall and a 7+/10 pursue threshold. Uses live public web evidence and cites every claim. Curate the score to your own bus
search_scientific_evidence ~396 tokens
Retrieve verifiable academic and engineering literature for a technical topic so a claim can cite a resolvable DOI instead of a vendor blog post. Queries Semantic Scholar (citation graph, abstracts, open-access PDFs) and the arXiv preprint index, merges duplicates, and ranks by citation count then r
teardown_product_spec ~669 tokens
Deconstruct a physical hardware device, battery pack, medical system, or software API into an institutional-grade technical specification table with exact units, tolerances, verified images/diagrams, datasheet links, certifications, and displacement seams.
teardown_tech_stack ~526 tokens
Deconstruct an account's technical infrastructure, dev tools, cloud providers, AI/data stack, and identify displacement vulnerabilities.

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