Three things, all one MCP call away: custom datasets anyone can create and query, 24k+ companies scored for agent readiness, and Vetted AI researchers, engineers, founders with person-AR scores and recruiter-ready tooling.
Upload a CSV, any schema. We auto-embed every row for semantic search, push updates via HMAC-signed webhooks, and expose keyword + per-column + natural-language queries through a single MCP surface your agents already know how to call.
create_custom_dataset — any shape, any schema, live in secondsquery_custom_dataset — keyword ILIKE, per-column filters, all server-sidesemantic_search_dataset — pgvector cosine, scoped to your datasetrow_updated / new_claim — push, not poll// Create a dataset from any CSV, get a stable id back Use OnlyData: create_custom_dataset({ name: "Sturdy top-50 prospects", csv: "name,domain,segment,...\n..." }) // Query it three ways: Use OnlyData: query_custom_dataset({ dataset_id: "...", search: "fintech boise", filters: { segment: "financial_services" } }) Use OnlyData: semantic_search_dataset({ dataset_id: "...", query: "local banks with complex treasury ops" })
We scan every company's homepage, llms.txt, mcp.json, OpenAPI spec, and structured data
signals — then blend them into a 0–100 AR score. Open layer, MCP-native, updated daily. Get context on a company
before your agent loads their tab.
company_brief — AR score, AI-native classification, ecosystem rolescan_agent_readiness — scan any URL on demand, get the reportsearch_businesses — filter by industry, location, AR score rangesemantic_search — "show me AI-native fintechs with llms.txt"// One call before any recruiter / sales / partner conversation Use OnlyData: company_brief({ domain: "airbnb.com" }) // → returns: { name: "Airbnb", agent_readiness_score: 47, ai_native: "integrated", agent_ecosystem_role: "consumer", super_category: "Travel & Hospitality", team_members: [/* ... */], signals: { llms_txt: false, mcp_json: false, openapi: true, structured: true } }
Vetted active AI researchers, engineers, founders — seeded from arXiv bylines, top OSS contributors, and opt-in program rosters (MATS, Apart). Every row scored on 5 dimensions with source-aware archetype floors. Filter by transition state (just-left, founding, building). Post a job, get ranked candidates with contact paths.
post_job_opening + match_candidates_for_job — ranked in one callai_minds_at_company — "who's at Anthropic, who's leaving, who's founding"query_custom_dataset with transition_status + contactable filters// Recruiter flow: post a role, get ranked candidates Use OnlyData: post_job_opening({ company_name: "Contoso AI", title: "Founding Research Engineer — Interp", description: "mech interp + SAE + evals", role_type: "research_engineer", compensation_max_usd: 320000 }) // → then: Use OnlyData: match_candidates_for_job({ job_id: "...", only_transitioning: true, require_contact: true, limit: 10 })
Two paid slots a year at $20k/mo. We embed with your team — treat your company the way we treat OnlyData: MCP-native, agent-first, every surface callable by an LLM. One slot is live with Sturdy (BuildOps-adjacent ecosystem work). The other is open. Plus two mentorship tiers (unpaid, Boise-first) with limited spots.
// Week 1 — audit scan_agent_readiness({ domain: "yourco.com" }) company_brief({ domain: "yourco.com" }) // → score, gaps, adjacent ecosystem // Weeks 2-4 — ship the spine create_custom_dataset({ csv: "your first-party data" }) // → MCP-queryable, webhooked, embeddable // Month 2+ — agent surface + team enablement // your CEO and PMs call your own data // from Claude, Cursor, Raycast — no new UI.
Every surface above — custom datasets, company AR, person AR, recruiter tooling — is an MCP call. Your Claude / Cursor / Raycast / Rally / Ampcode agents already know how to reach it. No new dashboards, no new logins, no scrape-and-paste pipelines. Your agent writes the query, OnlyData returns the answer, the evidence stays public.