Canonical Company Search

Canonical finds the companies others miss — the long tail.

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Что умеет

Search Companies: Search Canonical's verified company graph for the long tail — the companies others miss. This is precise, LLM-verified company discovery, not a web search that returns ranked links.
Find Similar Companies: Find companies similar to a given company by domain. Args: company_domain: Domain of the seed company (e.g. "stripe.com") top_k: Number of similar companies to return (1-100, d
Get Company Details: Return the full detail payload for one canonical company by domain. Use this AFTER a search to drill into a specific company. Returns: - `company`: full canonical fields (name, do

Какие данные видит

Нужен ли аккаунт

Не нужен: сервер работает без входа

Canonical finds the companies others miss — the long tail. Unlike web search that returns links to crawl and rank, it's a verified company graph: describe what you want in plain English (or pass structured filters) and it retrieves from a corpus of millions, verifying each match against products, target customer, and business model with an LLM. Results come back keyed by domain, so an agent can walk the graph — search for companies, find look-alikes, pull a company's profile, disambiguate a name. Built for sales prospecting, recruiting, and market research.

Список инструментов сервера (5)

Технические названия из tools/list. Нужны только разработчикам.

search_companies	Search Canonical's verified company graph for the long tail — the companies others miss. This is precise, LLM-verified company discovery, not a web search that returns ranked links. `description` is the only fuzzy / semantic field: it expresses a free-text concept (e.g. "enterprise SaaS for supply-chain visibility"), which is passed to an LLM verifier that checks each candidate against the intent and returns a verdict. Everything else is an exact, hard filter — the pipeline enforces it before the verifier sees a result. IMPORTANT — unsupported constraints: there is intentionally NO field for constraints we cannot enforce (founder demographics, profitability, YC / accelerator batch, individual revenue figures). If the user asks for one, tell them it isn't a supported filter rather than pretending it was applied — or fold the idea into `description` for loose semantic verification. For example "YC S22 company" → description="Y Combinator Summer 2022 batch startup", which the verifier will check loosely. Args: description: Free-text semantic concept describing what the company does. This is the ONLY fuzzy field — the LLM verifier reads it and checks each candidate for match/partial/irrelevant. Examples: "B2B SaaS for HR teams", "consumer fintech targeting millennials", "climate tech in renewable energy storage". Omit (or pass null) for purely filter-driven searches (e.g. "all Series B companies in India with 50-100 employees"). cities: Restrict to companies headquartered in these cities. Exact match (case-insensitive). Example: ["San Francisco", "New York"]. For a metro/region, list all constituent cities and include common name variants (e.g. Gurgaon/Gurugram, Bengaluru/Bangalore). states: Restrict to these states/provinces. Example: ["California", "New York"]. Use full name, not abbreviation. countries: Restrict to these countries. Expand geographic regions to their constituent countries before passing — e.g. "Southeast Asia" → ["Indonesia", "Vietnam", "Thailand", "Philippines", "Malaysia", "Singapore"]; "Nordics" → ["Sweden", "Norway", "Denmark", "Finland", "Iceland"]. Single country: ["India"]. employee_size: Headcount band. One of: "1-10", "11-50", "51-100", "101-500", "501-1000", "1001-5000", "5001+". For "well-funded startup" signals, use funding_min_usd instead. funding_series: One or more funding-round labels to include. Values: "pre_seed", "seed", "series_a", "series_b", "series_c", "series_d", "series_e", "series_f", "series_g_plus", "growth", "late", "bridge", "venture", "angel", "other". funding_min_usd: Minimum TOTAL funding raised (USD). Heuristics: "well-funded startup" ≈ 50_000_000; "unicorn-range" use funding_post_money_min_usd instead. funding_post_money_min_usd: Minimum post-money valuation (USD). Heuristic: "unicorn" ≈ 1_000_000_000. funded_after: Only include companies that raised a round after this ISO date (YYYY-MM-DD). Example: "2022-01-01". funding_investor: Filter to companies backed by these investors. Pass the investor firm name; the server expands it to canonical variants and fund-family splits automatically. Example: "Sequoia" resolves to "Sequoia Capital", "Peak XV Partners", "Sequoia Capital India". You may pass multiple investors for an OR match. has_repeat_founder: True → require at least one founder who has previously founded or co-founded another company. has_technical_cofounder: True → require at least one technical co-founder (CTO/engineering background). requires_role_types: Restrict to companies where at least one person on record holds one of these roles. Values: "founder", "cofounder", "ceo", "cto", "cfo", "coo", "chief_other", "exec_other". founder_prior_categories: Restrict to companies whose founders previously worked at companies in these categories. Values: "faang", "big_tech", "unicorn", "top_startup", "mbb". founder_prior_companies: Restrict to companies whose founders previously worked at any of these free-text company names (resolved to canonical entities). exclude_company_domains: Domains to exclude from results. Use `lookup_companies` first to resolve names to domains when needed. Unresolvable domains appear in the response `warnings`. exclude_description: Semantic concept to EXCLUDE — any candidate the LLM judges as matching this description is filtered out. Example: "marketplace / platform businesses" to keep only direct-product companies. Combined with `description` for fine-grained positive+negative semantic shaping. intent: Optional ranking profile applied AFTER relevance filtering. Pick the slug that best matches the user's stated or implied use case from the surrounding conversation. Omit / pass null for relevance-only ordering. Allowed slugs and when to pick each: - "sales_prospecting": general outbound — user is building a top-of-funnel list of potential customers without a specific buying-window constraint. Optimizes for companies that are actively growing, hiring, and have brand reach (broad ICP fit). - "sales_timing": "who is buying NOW?" — user wants accounts with a near-term buying window. Optimizes for recent hiring acceleration paired with healthy growth (active investment / budget release). - "sales_expansion": user already has the customer relation- ship and wants accounts ripe for upsell, cross-sell, or deepening. Optimizes for stable, steadily-growing companies with strong retention. - "competitive_tracking": user has NAMED competitors and wants to monitor their direction. Optimizes for hiring- direction shifts, momentum, brand reach, and geo footprint. - "emerging_competitor_scan": user wants to DISCOVER new entrants / rising challengers they don't yet know about. Optimizes for fast-growing, aggressively hiring companies with rising visibility. - "talent_source": recruiter / hiring manager looking for companies to poach candidates from. Optimizes for hiring in the target function, alumni footprint, team pedigree, retention. - "recruiter_employer_vet": user is evaluating whether to send a candidate to a particular company ("is this a good place for my candidate?"). Optimizes for employer retention, stability, talent demand, and brand reach. - "jobseeker_stability": job seeker prioritizing job SECURITY over upside ("is this company safe?"). Optimizes for low churn, positive net flow, retention, moderate momentum. - "jobseeker_growth": job seeker prioritizing career GROWTH ("where can my career accelerate?"). Optimizes for high-momentum companies hiring into growth functions, strong talent magnetism, recent hiring velocity. top_k: Number of results to return (1-100, default 20). include_partials: When True, also returns LLM-evaluated "partial" matches (close but not strong). Off by default because partials aren't billed; opt in only when the user wants exploratory context beyond strong matches. Default False. When presenting results to the user, render each company's `domain` as a clickable link to the company's website (e.g. as a Markdown link to https://<domain>). Note: hard filters (location, funding, employee size, founder background, etc.) are applied exactly; `description` is the only fuzzy field, matched by an LLM verifier. Because each candidate is independently verified, the exact result set (and therefore the count and credits charged) can vary slightly between otherwise-identical calls — borderline matches may pass on one run and not the next. This is expected.
find_similar_companies	Find companies similar to a given company by domain. Args: company_domain: Domain of the seed company (e.g. "stripe.com") top_k: Number of similar companies to return (1-100, default 20) intent: Optional ranking profile that reorders the similar set AFTER similarity filtering — same taxonomy and selection rule as `search_companies` (pick the slug matching the user's use case; omit / pass null for relevance-only ordering). Intent only changes the ORDER of the matched set; it never changes which companies are in it, the candidate pool, or the credits charged. Use it for requests like "companies similar to Stripe that are hiring/growing fast" or "...ranked for who's buying now". Allowed slugs: - "sales_prospecting": general outbound ICP list. - "sales_timing": accounts with a near-term buying window. - "sales_expansion": existing customers ripe for upsell. - "competitive_tracking": monitor NAMED competitors' direction. - "emerging_competitor_scan": discover rising new entrants. - "talent_source": companies to poach candidates from. - "recruiter_employer_vet": vet a company for a candidate. - "jobseeker_stability": job security over upside. - "jobseeker_growth": career-growth / high-momentum companies. See `search_companies` for the full per-slug guidance. include_partials: When True, also returns LLM-evaluated "partial" matches (close but not strong). Off by default because partials aren't billed; opt in only when the user wants exploratory context beyond strong matches. Default False. exclude_company_domains: Optional list of company domains to exclude from the similar-companies results. Useful when the seed has obvious near-clones you want to skip (e.g. "similar to Stripe, not Square or Adyen"). Unresolvable domains appear in `warnings`. When presenting results to the user, render each company's `domain` as a clickable link to the company's website (e.g. as a Markdown link to https://<domain>). Note: each candidate is independently LLM-verified, so the exact set (and therefore the result count and credits charged) can vary slightly between otherwise-identical calls — borderline matches may pass on one run and not the next. This is expected and is not affected by `intent`.
get_company_details	Return the full detail payload for one canonical company by domain. Use this AFTER a search to drill into a specific company. Returns: - `company`: full canonical fields (name, domain, description, hq, employees, funding, dimensions). Includes `defunct` (bool) — when true the company has shut down, so don't route users to it. Always present when the domain resolves to a known company. Internal `id` fields are intentionally not included. - `people`: key people (cofounders + C-suite/execs — not only founders) with role, headline, LinkedIn URL, and `prior_companies` (each with category tags like 'faang', 'unicorn', 'top_startup', 'big_tech', 'mbb', and a `domain` handle you can pass back into this tool to walk the company graph). May be empty. - `leadership_data`: `"available"` (people populated), `"not_available"` (company is in our DB but not in the leadership subset — most companies fall here), or `"error"` (transient lookup failure). Free to call but rate-limited to prevent enumeration. When showing this to the user, render the `domain` as a clickable link to the company's website (e.g. as a Markdown link to https://<domain>). Args: company_domain: Domain of the company (e.g. "stripe.com") — the same handle returned in search results.
lookup_companies	Look up companies by name to disambiguate before another tool. Use this when a user names a company you'll feed into `find_similar_companies` (as a seed) or `search_companies` (as an `exclude_company_domains` entry) and the name might be ambiguous. Returns, per input name: - `candidates`: ranked (best-guess-first) list, each with `name`, `domain`, `headquarters`, `description`, `is_primary`, and `payload_richness`. - `confidence`: `"high"` (one entity) \| `"medium"` (a dominant entity among rivals) \| `"low"` (comparable rivals — a real toss-up). - `primary_candidate_domain`: the recommended domain, or `null` when asking. - `auto_resolve_recommended`: bool. Disambiguation policy — FOLLOW THIS: - If `auto_resolve_recommended` is true, proceed silently with `primary_candidate_domain` (the one candidate marked `is_primary`). Do NOT ask the user — the match is unambiguous (one entity, or a clear dominant one). - If `auto_resolve_recommended` is false, `primary_candidate_domain` is `null` and NO candidate is `is_primary` — none is authoritative. Present `candidates` to the user as a list and WAIT for them to pick before calling the next tool. Do not auto-select even if one looks right — disambiguation is the point. Free, rate-limited. Args: names: One or more free-text company names to look up. k: How many candidates to return per name (1-25, default 5). disambiguation_mode: Override the recommendation for non-interactive callers. "auto_when_confident" (default) follows the policy above; "always_auto" never asks (use the primary); "always_ask" always asks.
get_account_status	Return the authenticated org's credit balance, plan, and search rate limits. Use this to check remaining credits before issuing a search, or to pace requests against the org's per-minute and per-day limits. This call is completely free — it charges no credits and does not count against the search rate budget. Returns: - `credits`: bucket breakdown (`total`, `subscription`, `extra`) and `subscription_resets_at` (ISO datetime string or null) — when the subscription bucket will next be refilled. - `plan`: the org's current plan name (e.g. "free", "starter", "pro"). - `rate_limits`: `per_minute` and `per_day` search operation limits for the current plan. - `billing_url`: URL to the billing page to top up or upgrade.