MCP server

Agentery Official

com.agentery/agentery

Checked 25 Oct 2026, 20:29 UTC · Connected to it and listed its tools

Price benchmarks, alternatives & daily price history across 17,000+ AI agents and MCP servers.

Website

At a glance

Type

MCP server

Publisher

agentery.com (verified by the MCP Registry)

Status

Working at last check

Tools

23

Token cost

About 9,953 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

25 Oct 2026, 20:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http agentery https://agentery.com/api/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.agentery]
url = "https://agentery.com/api/mcp"

Gemini CLI

{"mcpServers":{"agentery":{"httpUrl":"https://agentery.com/api/mcp"}}}

Cursor

{"mcpServers":{"agentery":{"url":"https://agentery.com/api/mcp"}}}

VS Code

{"servers":{"agentery":{"type":"http","url":"https://agentery.com/api/mcp"}}}

Antigravity

agy mcp add agentery https://agentery.com/api/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"agentery","server_url":"https://agentery.com/api/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"agentery","server_url":"https://agentery.com/api/mcp"}

Tools

• compare_providers ~773 tokens
  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 c
• create_custom_benchmark ~446 tokens
  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
• delete_custom_benchmark Deletes data · ~93 tokens
  Disable access to a custom benchmark. Keeps only a minimal audit record; no underlying Agentery data is touched. Pass `benchmark_id`.
• demand_signals ~285 tokens
  Inspect searches by external callers in the last 90 days that found no provider or only weak matches (best relevance below 0.62), shown as generalised job labels and ranked by distinct callers. Most entries come from a single caller: treat those as leads. These are limited coverage signals from Agen
• find_market ~306 tokens
  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 l
• get_custom_benchmark ~268 tokens
  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 `benchmar
• get_group_fair_price ~302 tokens
  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
• get_price_index ~497 tokens
  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
• get_price_index_history ~636 tokens
  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|
• get_provider ~152 tokens
  For buying decisions prefer get_provider_profile (prices, deployment, evidence); use this only for the short 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.
• get_provider_profile ~289 tokens
  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 co
• get_research ~235 tokens
  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
• market_gaps ~359 tokens
  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 = un
• market_report ~569 tokens
  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
• price_benchmark ~1147 tokens
  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 deli
• refine_results ~429 tokens
  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
• report_outcome ~499 tokens
  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, im
• request_research ~347 tokens
  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
• research_capability ~808 tokens
  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 i
• search_providers ~936 tokens
  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), deliv
• stop_research_updates ~64 tokens
  Stop watching a research job (the result stays retrievable with get_research).
• suggest_alternatives ~360 tokens
  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
• update_custom_benchmark ~153 tokens
  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`.

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