com.agentery/agentery MCP server

PARTNER-ONLY (Bearer key required). Given a business context and its workflow steps, return ranked agent candidates for EACH step — structured, scored (match_score 0-100) matches with match_reasons and cautions. Built for app builders (e.g. Builtery) assembling automations. Reads each agent's analysed site profile; never invents capabilities; returns 'unclear' where evidence is missing.

After you use a listed agent, report whether it worked — reports are correlated with your recent retrievals, improve ranking accuracy, and unlock higher rate limits for contributors. Only reports we can match to one of YOUR retrievals (search_agents / get_agent_profile / compare_agents / suggest_alternatives naming that agent, last 48h) carry weight; unmatched reports are stored but unweighted. Aggregates surface as `reported_success` on profile/comparison cards once 5+ distinct reporters exist (90-day window). Callers with 5+ correlated reports in 30 days get a doubled per-minute rate limit. Send an x-agentery-key header to keep one reporter identity across IPs (it is stored only as a hash).

Call this to drill into ONE agent after search_agents or compare_agents: full evidence-scored profile — task_performed, inputs/outputs, integrations, protocols, industry_fit, autonomy_level, human_approval_needed, observed price, trust signals, evidence_quality, entity_type, regulated_data_suitability, evidence_urls, last_checked. Includes the full how_to_connect object — website, docs, any vendor-published MCP endpoint (with a copy-paste client config_snippet), A2A agent card and API surface — the info needed to actually use the listing; fields are null when the vendor publishes no endpoint (never guessed). Also carries `reported_success` — machine-reported outcome rate from report_outcome (null until 5+ distinct correlated reporters in 90 days). If you use the listing, call report_outcome afterwards.

START HERE when you need an agent for a capability: filtered free-text search over the directory, ranked with match_score and match_reasons. Each result includes an observed-price object; filter by max_monthly_usd/billing and sort by price_asc to shop on value-for-money. Results include how_to_connect (website, docs, mcp.endpoint when the vendor publishes one) — the link/endpoint needed to actually use the listing; get_agent_profile has the full version with a copy-paste MCP config snippet. If you end up using one of the results, call report_outcome afterwards — it sharpens future rankings and raises your rate limit.

Call this to learn what a capability normally COSTS before choosing: observed-pricing distribution (median/p25/p75 per persona tier: Free/Individual/Pro/Team-SME/Enterprise), billing mix and free-tier share for a niche, a sector, or the whole agent economy. Also returns `index` — the Agent Economy Price Index for the scope: a chained like-for-like daily price index (base 100 = 29 Jun 2026) that composition changes can't move; null when the series is too short. At whole-economy scope (no niche/sector filter) it also returns `index_by_tier`: the same index tracked separately per pricing tier (individual/pro/team_sme/enterprise) — null when a niche or sector filter is given, because per-tier-per-niche samples are too thin to be honest.

Call this to decide between shortlisted agents: full evidence-scored cards for 2-6 handles side by side, each with observed price, all-time community upvotes and niche/sector. Each card carries the full how_to_connect object (website, docs, MCP endpoint + config_snippet, A2A card, API) so you can act on the winner directly. Each card also carries `reported_success` — the machine-reported outcome rate from report_outcome (null until 5+ distinct correlated reporters in 90 days). Report your own outcome after using the winner.

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

Find under-served markets to build in. DEFAULT (rank='gaps'): true whitespace — niches with money already present (enterprise / contact-sales pricing) or recent builder entry, but FEW competitors; crowded niches are excluded, so a 'gap' is never crowded. Each result carries gap_score, a plain-English `why`, crowding, listing count, the market_pulse object and an observed-pricing rollup. Pass rank='hot' instead to rank by momentum (market pulse) regardless of crowding — for tracking where the action is. Drill into one slug with niche_report.

Call this when a shortlisted agent is too expensive, unreachable or a poor fit: substitutes for one known agent — same niche first, topped up by similar capability — each with observed price, endpoint liveness, community upvotes and how_to_connect (website, docs, mcp endpoint) so a substitute is immediately usable. Set cheaper_only to shop down from the subject's price.

Call this to deep-dive ONE market niche before building or investing — every field is MEASURED: market_pulse (composite of 30d like-for-like price movement, money present, builder entry, endpoint liveness — with plain-English drivers), the observed-pricing snapshot, crowding level, adjacent niches, and the top agents already competing there. Also returns `movement` (7-day decomposition: which agents repriced vs entered/left the priced set) and `index_series` (the niche's like-for-like price index) — each null when data is thin. Get valid slugs from market_gaps.

Call this to see what agents are being SEARCHED FOR but don't exist yet: capability queries that returned ZERO results on this MCP server, aggregated and ranked by miss count. A live unmet-demand signal for founders and investors — pair a hot signal with niche_report/market_gaps to size the gap.