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Agent.ai

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Agent builderindependentVerified 2026-07-01

A marketplace and network of hundreds of prebuilt AI agents plus a low code builder, created by HubSpot cofounder Dharmesh Shah, where every agent gets a programming interface automatically.

Agent.ai is a marketplace and professional network for AI agents, created by Dharmesh Shah, the cofounder and chief technology officer of HubSpot. Launched at INBOUND in 2024 and run independently of HubSpot, it grew quickly to more than a quarter million registered users. Shah describes it as the professional network for AI agents and frames a future of hybrid teams where humans and AI agents work side by side. Users can browse, test, hire, and deploy agents for a single task or on an ongoing basis, and everything is free to start with a hundred credits and a pay per task credit model.

The heart of Agent.ai is its network of hundreds of specialized agents, each combining existing AI services like building blocks. Popular examples include a Company Research Agent that compiles a company dossier by pulling from Google, OpenAI, HubSpot, and Perplexity in about a minute, a conversion rate optimizer that critiques a web page, and briefing agents that chain to other agents. Approved builders and partners can publish their own agents to the network, which Shah likens to how the App Store expanded the iPhone.

Alongside the marketplace sits a low code Agent Builder that lets teams create their own agents from simple building blocks, and a spread of models is a first class feature. Agent.ai spans every major model, letting users pick GPT for reasoning, Claude for writing, or Gemini for long context, and its agents route across services accordingly. Extensibility is a genuine strength. Every agent published to Agent.ai automatically exposes a REST programming interface and appears in a Model Context Protocol server, so it can be invoked from anywhere in any form.

Agent.ai is deliberately lightweight and accessible rather than a heavy enterprise platform. Its tasks skew toward research, content, analysis, sales, and marketing use cases, and outputs, like any generative system, benefit from human fact checking. Enterprise controls such as named security certifications, runtime guardrails, deep observability, and shipped cross agent memory are not yet its focus, though Shah has written and spoken about cross agent memory and finer grained data sharing as priorities. It is best understood as the fastest way to discover, try, and combine a large library of agents.

Vendor details

Canonical URL

https://agent.ai

Company status

independent

Use cases & customers

In practice

A sales rep needs to prep for a meeting fast. Agent.ai's Company Research Agent compiles a dossier on the prospect, pulling founders, funding, press, and web traffic from several services in about a minute rather than hours of manual browsing.

A marketer wants to lift conversions. They run a page through Agent.ai's conversion rate optimizer, which grades the copy and suggests specific changes to phrasing, calls to action, and imagery, then tries a few competing agents to compare.

A builder wants an agent callable from their own tools. They assemble one in Agent.ai's low code builder, and it automatically gains a REST interface and a Model Context Protocol entry, ready to invoke anywhere.

Sources & related URLs

Research notes

Agent MARKETPLACE + low-code builder by Dharmesh Shah (co-founder/CTO HubSpot). Launched INBOUND Sept 2024; runs INDEPENDENT of HubSpot (Shah hopes it joins HubSpot ecosystem eventually, like ChatSpot→Breeze). 230-258k+ users by Jan 2025 (past 100k target). 280+ agents (Shah built 17). 'The #1 (only) AI Agent Marketplace'; 'professional network for AI agents'; hybrid-teams vision. FREE, 100 credits to start, pay-per-task (1 credit/task). Core: browsable network of specialized agents (research/writing/SEO/logos/content); users scout/test/hire/deploy; publishers/partners publish agents (iOS App Store analogy). Popular: Company Research Agent (dossier from Google/OpenAI/HubSpot/Perplexity ~60s), CRO Agent, Customer Briefing Agent (chains to other agents). Agent Builder (low-code, combine AI services 'like Lego'). MODEL: 'every AI model, one place' — GPT (reasoning)/Claude (writing)/Gemini (context)/o3 (F). EXT (STANDOUT): every agent AUTO gets a REST API + AUTO shows in MCP server, invokable anywhere (F). Mem: cross-agent memory sharing is Dharmesh's VISION/thesis, not clearly shipped (N). Lightweight/prosumer: no certs/HITL/observability/on-prem/computer-use (6 N's). Tasks skew research/content/sales/marketing (not deep transactional autonomy). Accuracy needs fact-checking. Domain agent.ai. Score 5.5 (3F/5P/6N) — Pack+Model+Ext Full; lightweight elsewhere.

Capability coverage

5.5 / 14 capabilities · 39%

Integrations & Tool CallingAgent.ai agents chain external services like Google, OpenAI, HubSpot, and Perplexity together like building blocks, real integration and tool use short of deep enterprise system read and write actions, so partial.	Partial
Workflow OrchestrationAgent.ai agents chain multiple steps and even call other agents to accomplish multi step goals like research and briefing, real orchestration short of deep autonomous system action taking, so partial.	Partial
Knowledge Grounding & RAGAgent.ai agents gather and ground information from web search and services like Perplexity and Google for research tasks, real grounding short of documented reliable citation level attribution, so partial.	Partial
Human Oversight & GuardrailsAgent.ai lets users scout, test, and pick agents while builders set usage policies, but a first class runtime human oversight or guardrail enforcement framework could not be verified.	Unable to verify
Security, Identity & GovernanceAgent.ai is a free agent marketplace and builder, but named security certifications such as SOC 2 could not be verified.	Unable to verify
Observability & AuditabilityAgent.ai lets users test agents before use, but a documented observability or audit trail for agent actions could not be verified.	Unable to verify
Memory & State PersistenceAgent.ai's founder emphasizes cross agent memory sharing as a direction, but a shipped first class persistent cross session agent memory could not be verified.	Unable to verify
Deployment & Data ResidencyAgent.ai is a hosted marketplace and builder platform, but a self host, on premises, or dedicated data residency deployment could not be verified.	Unable to verify
Prebuilt Agents, Templates & PacksAgent.ai is a browsable marketplace network of hundreds of specialized prebuilt agents that users can discover, test, and deploy, with publishers adding more, so full.	Full
Triggers & Channel CoverageAgent.ai agents run on demand through a web interface and can be invoked programmatically, real trigger coverage short of broad omnichannel deployment, so partial.	Partial
Model Flexibility & RoutingAgent.ai spans every major model, letting users pick GPT, Claude, Gemini, and others across agents, so full.	Full
APIs, SDKs & MCP ExtensibilityEvery agent on Agent.ai automatically exposes a REST application programming interface and appears in a Model Context Protocol server for invocation in any form, so full.	Full
Testing, Debugging & OptimizationAgent.ai lets users test and evaluate multiple agents before deploying, picking the best for a use case, real evaluation tooling short of a documented simulation or automated scoring framework, so partial.	Partial
Browser & Computer UseAgent.ai agents analyze web pages and content by URL, but general browser or computer use as a first class capability could not be verified.	Unable to verify

Recent platform changes

No recent material changes tracked yet.

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Pricing

Free to start (100 credits), ~1 credit per task

Public — exactMedium variable cost

Verified 2026-07-01

Data confidence: high