Agentery

Use for a quick first overview of a buying task in one call: the closest-matching listings (matched on what they do, no fixed categories), the price range and median for comparable products (with n), and a shortlist with observed prices, market_position (below / in line / above market) and handles in compare_ready for compare_providers. Also returns suggested_alternatives. It does not run the comp

Use when someone wants to find or shortlist AI products, AI agents, MCP servers or APIs for a task, e.g. 'AI tool that transcribes sales calls' or 'MCP server to reply to Zendesk tickets'. Returns ranked candidates with what each does, a fit label (match / partial / weak, naming any mismatch), delivery type, price status (known / free / contact_sales / unknown; unknown is never free) and links. Re

Use when someone asks what a kind of product typically costs or who competes in a space, e.g. 'what should I charge for lead-generation automation' or 'tools that monitor competitor pricing'. Maps the task to its market (the nearest providers by meaning, no fixed categories) and returns the market label, provider and priced counts, the nearest providers with observed prices, and pricing_by_tier (m

Use to compare 2–6 shortlisted listings side by side — plan-level prices (e.g. the Pro tier), capabilities, deployment, licence and how to connect — or to check a quote against alternatives. Inputs resolve to real listings by exact handle, then exact name, never a silent fuzzy swap: unknown inputs come back in unresolved_inputs with suggested_matches and a corrected_call; if only one input is real

Use when asked whether prices of AI agents, tools or MCP servers are rising or falling overall. Returns the current Agent Economy Price Index (AEPI), a like-for-like index of observed agent and MCP pricing (base 100 = 29 Jun 2026; an index level, not a price), with 1-, 7- and 30-day change, plus the same for the four buyer tiers (Individual, Pro, Team/SME, Enterprise). provider_type=agent|mcp give

Use to judge whether a price is fair or what a capability typically costs, e.g. 'Is $49/month reasonable for an AI SDR for a small team?'. Pass the capability as `query` (aliases: task, niche). Returns observed prices of comparable products — median, p25/p75, range, mean, stdev and n — split by delivery type (agent | mcp) and buyer tier (individual / pro / team_sme / enterprise), never blended acr

Use when a buying decision hinges on one specific fact about one listing that its profile does not settle, e.g. {"provider_id":"flux_operator","requirement":"Is there a Helm chart for Kubernetes?"} or 'Does the Business plan go to checkout or to contact sales?'. Agentery reads the vendor's own pages, its code repository (read, never run) and the pricing page's buttons, and answers yes / no / partl

Status and result of a research job created by request_research. status: queued / running / answered / partly_answered / still_unknown / failed; phase: queued | running | retry_scheduled | completed_answer | completed_unknown | failed. Poll no more often than poll_after_seconds — polling is free and never repeats the work. result: answer (yes/no/partly/unknown), short_answer, evidence per claim (q

Stop watching a research job (the result stays retrievable with get_research).

Use when an earlier search_providers or research_capability answer missed what was meant: pass its request_ref and the correction in plain words (e.g. 'must integrate with Slack', 'budget is $20/month', 'data must stay in the EU'). Agentery re-runs the search with the changed constraints (the others are kept) and returns the new answer plus what changed. source: 'human' (the user's words), 'agent'

Use to check what a product of a given kind typically costs: give a task or product type (or a group_id from the group price league) and get its product group's fair price for each buyer tier (individual, pro, team / small business, enterprise) — the median entry monthly price in that tier with its typical range — plus which payment models the group typically uses (free, subscription, usage, one-t

Use to show how AI agent and MCP prices have moved over time: the dated Agent Economy Price Index series, the same chained like-for-like series agentery.com/aepi charts. Points are index levels (base 100), never prices. Whole-economy series by default; `tier` for one buyer tier; provider_type agent|mcp for one delivery type (own base 100); `period` 30d (default) / 90d / all; response_mode summary

Use when a seller or investor asks which tasks people look for that few paid products serve. Clusters requests seen on this MCP server by meaning and returns those far from any paid provider: the request phrasing, distinct_callers, raw_requests, the nearest paid provider and its similarity (low = under-served). headline = jobs asked by two or more callers; weak_leads = one caller; information_requ

Find related alternatives to a known provider, ranked by text-embedding nearness to that provider's OWN profile (NO category lookup), each with observed price, endpoint liveness, community upvotes and how_to_connect (website, docs, mcp endpoint). For cheaper_only, inspect whether the reference price and candidate prices support a valid comparison: an empty response may reflect a missing or incompa

Inspect eligible zero-result or weak-match capability queries observed on this MCP server, aggregated and ranked by miss count. These are limited coverage signals from Agentery's own callers — not proof that a product does not exist, and not proof that a market has paying demand. Not a prerequisite for choosing a product. Empty args ({}) return the current list; an empty response means there is in

Report the result of ACTUALLY USING a listed provider for a task. Testing Agentery's connection or retrieval does not establish that the listed provider worked — do not report those. Reports are self-reported evidence subject to eligibility checks: they are correlated with your recent retrievals, improve ranking accuracy, and unlock higher rate limits for contributors. Only reports we can match to

Use to check one specific listing before recommending or connecting it: plans and prices with billing units, what it does, integrations, deployment (hosted / self_hosted / both / unknown, with evidence), licence (named licence only), liveness and how to connect (website, docs, MCP endpoint with a copy-paste config_snippet, A2A agent card, API, install). Fields are null when the vendor publishes no

Call this for the public directory card of one provider by handle or registration number: bio, source URLs, X-verification status, entity type, community rating and structured profile when available.

Deep-dive ONE market before building or investing — the market is the semantic neighbourhood of your natural-language query (nearest providers by text embedding, NO fixed category). Every field is MEASURED: the observed-pricing benchmark separated by provider type and buyer tier (median, mean, stdev, p25/p75, min–max range and n via the canonical pricing engine), how many providers are in the neig

Use when someone wants to keep watching the prices of products they choose (e.g. five named writing tools). Creates a PRIVATE custom benchmark (a saved, calculated peer cohort) over Agentery's data — no account needed. Two modes: (A) explicit members: pass `members` (a list of exact handles; product names/domains resolve where unambiguous). (B) fork a market: pass `base_niche` (its slug) plus opti

Get a private custom benchmark's current report: members, current stats (headline median/quartiles only when ≥3 comparable priced members — monthly, per-seat and per-call prices are never blended), buyer-tier / provider-type / pricing-unit cohorts, historical index, and data coverage. Pass `benchmark_id` (your cb_ token) as an ARGUMENT.

Add/remove members or rename a custom benchmark. Creates a NEW immutable version (the previous version stays fully reproducible) and returns the exact change-impact on the median/quartiles/index. Pass `benchmark_id`.

Disable access to a custom benchmark. Keeps only a minimal audit record; no underlying Agentery data is touched. Pass `benchmark_id`.