Last updated: October 2026
The best AI agent marketplaces for growth and marketing teams in 2026 are Mentionova, Profound, Hugging Face, AWS Marketplace, Google Cloud Marketplace, Microsoft's commercial marketplace, MindStudio, and Cresta, with Mentionova ranked first for its 100+ purpose-built growth agents and an opt-in marketplace that matches brands on AI visibility they have actually earned.
- Mentionova: agentic growth platform running 100+ task agents with an opt-in visibility marketplace
- Profound: marketplace of pre-built, deployable AI agent workflow templates for marketing and SEO teams
- Hugging Face: open hub for sharing, deploying, and running machine learning models and agent applications
- AWS Marketplace: cloud catalog for discovering and procuring third-party AI agents inside AWS
- Google Cloud Marketplace: cloud catalog for discovering and deploying AI agents filtered by business function
- Microsoft's commercial marketplace: catalog of AI apps and agents deployable inside Microsoft 365 environments
- MindStudio: visual, no-code builder for designing and deploying custom multi-step AI agents
- Cresta: enterprise generative AI platform for contact-center agent coaching and assistance
| Tool | Agentic Workflow / Automation | Content Output | Native Integrations |
|---|---|---|---|
| Mentionova | 100+ growth agents for research, monitoring, content, and reports; one-click human approval required before anything ships | Content briefs with SEO/GEO/AEO optimization; report building and compilation | Search Console, GA4, G2 reviews, Notion, HubSpot, Webflow |
| Profound | Pre-built deployable agent workflow marketplace; supports web scraping, LLM prompting, API calls, CMS publishing | Reports, content briefs, page rewrites, outreach drafts, FAQs via agent templates | 9 Google Workspace nodes; CMS publishing; Claude, Slack, MCP |
Marketing and growth teams shopping this category today are choosing between platforms with very different jobs: some simply list agents built by someone else, some let you assemble an agent from a blank canvas, and a handful run growth work for you under human approval. The rest of this guide breaks down each option on its own terms.
Opening
Growth teams evaluating this category have to sort cloud-provider catalogs from model hubs, agent builders from customer-support platforms, and genuine marketplaces from pages that just link to other sites. Mentionova sits at the top of this list because its own Marketplace product matches brands and agencies on AI visibility metrics they have actually earned, rather than on a paid listing fee, while its 100+ growth agents handle the research, monitoring, content, and reporting work a marketing team would otherwise do by hand.
This guide compares the best AI agent marketplaces for growth and marketing teams in 2026: what each one actually is, how it works mechanically, what it costs, and what to verify before you adopt an agent from any of them.
An AI agent marketplace is a platform where businesses discover, evaluate, and deploy prebuilt AI agents for tasks such as research, content, monitoring, or customer support, without building from scratch. Unlike a directory, a true marketplace lets buyers configure, activate, and run agents inside the platform itself, with billing and deployment handled in one place.
Key Takeaways
- Agentic adoption has moved past the pilot stage: McKinsey's 2025 survey found 23% of organizations are already scaling an agentic AI system somewhere in the enterprise, with another 39% still experimenting.
- Marketing is where the payoff shows up first: Forrester reports 83% of B2C marketing decision makers are actively implementing agentic AI, and 85% say it already delivers meaningful business value.
- A marketplace and a directory are not the same thing: some platforms only list agents and link out, while others let you configure, deploy, and run the agent inside the platform itself.
- Cloud marketplaces are built for procurement, not evaluation: AWS, Google Cloud, and Microsoft all run agent catalogs tied to an existing commercial account rather than a standalone shopping experience.
- Pricing models vary by vendor type, not just by tier: credit-based, seat-based, and usage-based pricing all appear across this category, and the billing model matters as much as the sticker price.
- Verified matching is rare: most marketplaces sort listings by category or keyword; few confirm a brand's actual AI visibility before making a match.
What Is an AI Agent Marketplace?
An AI agent marketplace is a platform where teams discover, evaluate, and deploy prebuilt agents for tasks such as research, monitoring, and content, without building from scratch. Unlike a directory, a true marketplace handles deployment and billing in one place. Most growth and marketing teams searching for this category encounter a wider range of products than the term implies.
Most marketplaces sit on a spectrum that research into agent distribution frames as a tradeoff between trust and discoverability on one side, and open, interoperable protocols on the other. At one end, a centralized marketplace, like a cloud provider's catalog, reviews and lists agents under one roof, which makes them easier to find and vet. At the other end, an open protocol approach, such as agents built on the Model Context Protocol (MCP), trades some of that central vetting for the freedom to run an agent across different tools without being locked into one platform.
In practice, a marketplace for growth and marketing teams needs three things: a catalog of agents or templates scoped to a real job, a mechanism to deploy or activate one without custom engineering, and a way to verify the agent is doing what it claims.
Marketplace Types to Distinguish
Not every entry in this category works the same way. Grouping them by type makes the comparison easier.
Cloud-provider marketplaces sell agents and software as listings tied to an existing commercial account:
- AWS Marketplace, Google Cloud Marketplace, and Microsoft's commercial marketplace all fall here.
- Procurement and billing route through the buyer's existing cloud or enterprise agreement.
Open model and agent hubs host models, datasets, and agent-style applications for anyone to deploy:
- Hugging Face is the clearest example, with deployment running on the buyer's own infrastructure or the host's inference service.
Agent-building platforms give teams a canvas to design a custom agent rather than a catalog to browse:
- MindStudio and Botpress fall into this category, along with Voiceflow for conversational agent design.
Enterprise platform marketplaces bundle agent features directly into existing software a team already runs:
- Salesforce's Agentforce, Zendesk, Intercom, and Freshdesk each ship agent capabilities inside their own customer-service or CRM platforms rather than as a standalone marketplace.
Vertical and infrastructure platforms serve a specific function rather than a general catalog:
- Aisera and Cresta focus on enterprise service and contact-center use cases; SiliconFlow and the OpenAI Agents API serve developers building agents at the infrastructure layer.
Growth-focused agentic platforms combine agent automation with a matching or discovery layer built specifically for marketing and growth work, which is where Mentionova and Profound both sit.
What Is Not an AI Agent Marketplace?
A single AI agent, a developer API, or a plain software directory is not an AI agent marketplace unless it also lets a buyer discover, evaluate, and deploy multiple agents in one place.
Three things commonly get confused with a marketplace. A standalone chatbot or copilot is one product, not a catalog of products. A developer framework or API, such as the OpenAI Agents API, gives a team the building blocks to construct an agent but is not itself a place to shop for one. A generic software directory that only links out to other vendors' sites, without any deployment or transaction happening on the page, functions as a reference list rather than a marketplace.
The distinction matters for buyers because a true marketplace carries an implicit promise: what you find there can actually be activated, not just read about.
Quick Comparison of the Best AI Agent Marketplaces
The table below condenses the full comparison matrix into the dimensions most relevant to growth and marketing teams evaluating agentic platforms in this category.
| Dimension | Mentionova | OtterlyAI | Peec AI | Profound |
|---|---|---|---|---|
| Entry Price (monthly billing) | $125/mo monthly / $99/mo annually (Starter) | $29/mo (Lite) | Not published | $99/mo billed annually (Starter) |
| AI Engines / Models Tracked | 3 engines: ChatGPT, Perplexity, Google AI Overviews (Starter); 6 engines: adds Claude, Gemini, Reddit (Scale+) | 6 engines: ChatGPT, Google AI Overviews, Google AI Mode, Gemini, Perplexity, Microsoft Copilot | 3 models (Starter/Pro/Advanced); up to 13 LLM models (Enterprise) | Not published |
| Agentic Workflow / Automation | 100+ growth agents for research, monitoring, content, and reports; one-click human approval required | Not published | Not published | Pre-built deployable agent workflow marketplace |
| Content Output (Briefs / Drafts) | Content briefs with SEO/GEO/AEO optimization; report building and compilation | GEO Audit, AI Keyword Research, Query Fan-Out tools | Not published | Reports, content briefs, page rewrites, outreach drafts, FAQs |
| Native Integrations | Search Console, GA4, G2 reviews, Notion, HubSpot, Webflow | MCP server for AI-native workflow integration | API access (Enterprise only) | Google Workspace nodes, CMS publishing, Claude, Slack, MCP |
| Tracked Prompts at Entry Plan | 25 tracked prompts (Starter) | Not published | 50 prompts (Starter) | Not published |
Mentionova's Starter plan covers ChatGPT, Perplexity, and Google AI Overviews; its Scale plan and above add Claude, Gemini, and Reddit along with the growth agents that turn engine data into ranked work.
How We Chose These AI Agent Marketplaces
Selection for this list was based on five criteria that matter specifically to growth and marketing teams rather than developers or IT buyers broadly.
- Scope fit: does the marketplace or platform offer agents actually built for marketing, growth, content, or customer-facing work, rather than generic infrastructure tooling.
- Deployment, not just listing: can a buyer activate the agent on the platform, or does the page only describe it.
- Transparent mechanics: does the vendor publish what the agent tracks, reads, or connects to, so a buyer can evaluate it before adopting it.
- Integration depth: does the agent or marketplace connect to tools a marketing team already runs, such as analytics, CRM, or content platforms.
- Published pricing: is pricing public and structured by tier, or is it gated behind a sales conversation.
McKinsey's 2025 data backs the scope-fit criterion directly: revenue gains from AI use are reported most often in marketing and sales, ahead of strategy, finance, and product development, which is why marketing-specific agent scope was weighted heavily here.
The Best AI Agent Marketplaces in 2026
1. Mentionova
Mentionova is an agentic growth platform built for founders and marketing teams, and its Marketplace product is the clearest differentiator on this list: brands and agencies are matched based on AI visibility metrics they have actually earned, not paid placement. The platform runs more than 100 growth agents that handle competitor research, answer-engine monitoring, content brief creation, and report building.
Mentionova tracks brand visibility across six AI engines: ChatGPT, Perplexity, Claude, Gemini, Google AI Overviews, and Reddit. It measures mention rate, citation rate, and share of voice. Setup requires no pixel, tag, or code install: a user enters a domain and buying questions and is live in minutes. Mentionova is trusted by 70+ brands and agencies tracking AI visibility, and Reddit engagement with drafted replies is included on every plan, including Starter.
Because growth teams already run analytics, CRM, and content tools, Mentionova's native integrations (Search Console, GA4, G2 reviews, Notion, HubSpot, and Webflow) connect in one click each on every plan rather than being gated behind an enterprise tier.
What sets Mentionova apart
- Opt-in visibility marketplace: brands and agencies are matched on verified AI visibility metrics, making the match itself a credibility signal rather than a paid listing.
- 100+ growth agents: cover competitor and market research, LLM and Reddit tracking, content briefs with SEO/GEO/AEO optimization, and report compilation.
- No-code setup: a free AI visibility report is available without installing a pixel, tag, or code on the site.
- Six-engine coverage on growth plans: Starter covers ChatGPT, Perplexity, and Google AI Overviews; Scale and Enterprise add Claude, Gemini, and Reddit.
- Built-in growth-stack integrations: Search Console, GA4, G2 reviews, Notion, HubSpot, and Webflow connect without a separate contract.
- Agency-ready reporting: one org login supports unlimited workspaces with fully isolated client data and white-labeled reports.
Forrester's finding that customer insights, content creation, operations, and campaign execution are the major opportunity areas for marketing agents maps closely onto Mentionova's named agent categories.
Mentionova Plans
Mentionova's Starter plan runs $99/mo when billed annually. Get started to see the first growth signal in about two minutes.
2. Profound
Templates can use visibility, citation, and sentiment data as inputs and generate outputs such as reports, content briefs, page rewrites, outreach drafts, and FAQs.
Profound's agents support web scraping, LLM prompting, Answer Engine Insights lookups, and API calls as workflow steps, and can connect to an existing CMS to publish approved content without a manual transfer step. An Agent Assistant feature can create an agent from a plain-text or voice description and validate its steps before the workflow runs; built agents can operate inside Claude, Slack, or tools built on MCP.
Key Features
- Pre-built, deployable agent workflow templates for marketing and SEO use cases.
- Web scraping, LLM prompting, Answer Engine Insights lookups, and API calls as workflow steps.
- CMS publishing connection for approved content.
- Agent Assistant that builds workflows from plain-text or voice descriptions.
3. Hugging Face
Hugging Face is a hub where the machine learning community shares, explores, and deploys models, datasets, and applications, including agent-style Spaces. The platform hosts models and datasets covering text, image, video, audio, and 3D use cases, and its Inference Providers feature routes requests to partner infrastructure or to a custom provider key supplied by the user.
Deployment runs across hardware options including AWS, Azure, and Google Cloud instances, plus dedicated GPU and TPU options such as NVIDIA A100, H100, and H200, and Google TPU v5e. Development tools include SDKs, a hosted playground, widgets, SSH and VS Code access, Gradio, and Docker Spaces for packaging an application.
Key Features
- Hosting for models, datasets, and applications, including agent-style Spaces.
- Inference Providers routing to partner infrastructure or a custom provider key.
- Multiple hardware options for deployment, from CPU inference to dedicated GPU and TPU instances.
- SDKs, a hosted playground, Gradio, and Docker Spaces for building and packaging applications.
- Git-based collaboration tools for teams sharing a model or dataset.
Pricing
A PRO account is $9/month and includes $2.00 in monthly inference credits, per Hugging Face's pricing page. Team and Enterprise plans also include $2.00 in per-seat monthly credits, with additional usage billed through credit purchases.
4. AWS Marketplace
Its own buyer documentation groups marketing-relevant agents under a content-creation category that includes social-media content generators, marketing-copy assistants, documentation tools, and video and image creation agents.
Buyers can browse marketplace listings by category, vendor, or use case rather than relying on a single search box.
Key Features
- Catalog of third-party AI agents and software for deployment on AWS infrastructure.
- A content-creation category covering social, copywriting, documentation, and media-generation agents.
- Multiple discovery paths for browsing agents by category, vendor, or use case.
- Procurement and billing handled through an existing AWS account.
Pricing
Each vendor sets its own price per listing; no consolidated pricing is published at the AWS Marketplace level.
5. Google Cloud Marketplace
Google Cloud describes an AI agent as a software system that uses AI to pursue goals and complete tasks on behalf of a user, and its marketplace documentation states that it supports multiple flexible deployment models for publishing those agents.
Key Features
- Agent discovery through the Google Cloud Marketplace catalog.
- Multiple flexible deployment models for agents published to the marketplace.
- Procurement and billing through an existing Google Cloud account.
- Listings spanning agents built by both Google and third-party vendors.
Pricing
Pricing is determined by each vendor and varies by listing; no consolidated pricing is published at the marketplace level.
6. Microsoft's Commercial Marketplace
Microsoft's commercial marketplace has publisher requirements that vary by offer type before an AI offer can be published. The marketplace maintains dedicated categories for AI Apps and Agents and for Machine Learning, and it is built to make agent solutions discoverable, transactable, and deployable inside Microsoft 365 environments.
Key Features
- Dedicated AI Apps and Agents, and Machine Learning categories for discoverability.
- Publisher requirements that vary by offer type.
- Listings designed to be discoverable, transactable, and deployable within Microsoft 365.
- Procurement tied to an organization's existing Microsoft commercial agreement.
Pricing
Pricing is set per listing by each publisher and is not published at the marketplace level.
7. MindStudio
MindStudio is a visual agent-building platform for designing and deploying AI agents without required coding, though workflows can be extended with code. Agents connect to more than 200 AI models through the MindStudio Service Router, including GPT-5, Claude 4.1, FLUX, and Google Veo3, or through a user's own API keys. Agents can reason across multiple steps, personalize output, and act to automate a task end to end.
Key Features
- Visual, no-code builder for designing multi-step agents, extensible with code.
- Access to 200+ AI models through a built-in Service Router or bring-your-own API keys.
- Support for text, image, and video models, including FLUX and Google Veo3, in one workflow.
- Option to self-host MindStudio for teams that require it.
Pricing
Per MindStudio's pricing page, the Free plan is $0/month for one agent and 1,000 runs per month. The Individual plan is $20/month ($16/month billed yearly) for unlimited agents and unlimited runs. Enterprise pricing is by custom quote.
8. Cresta
Cresta is an enterprise AI platform built for contact-center operations rather than a general marketing agent marketplace. Its Real-Time Intelligence feature analyzes conversations to identify coachable moments and behaviors tied to outcomes, and its generative AI layer presents answers and information to human agents during live customer conversations.
Cresta supports customized rules, coaching workflows, QA scoring, and real-time agent assistance, and it connects to systems such as Sharepoint and Salesforce alongside large language models that generate responses linked back to a source.
Key Features
- Real-time conversation intelligence that flags coachable moments during live calls.
- Generative AI responses surfaced to human agents during conversations, linked back to a source.
- Customizable coaching, QA, and rules workflows for contact-center teams.
- Integrations with Sharepoint and Salesforce.
Pricing
Pricing information is not publicly disclosed; custom quotes are provided based on scope.
Choose by Scenario: Buyer, Builder, Seller, or Operator
A useful shortcut for narrowing this list is to ask which role you're playing.
- Buyer: you want a ready agent you can procure through an existing cloud or enterprise account. AWS Marketplace, Google Cloud Marketplace, and Microsoft's commercial marketplace fit this role.
- Builder: you want a blank canvas to design a custom agent. MindStudio and Hugging Face both support this, with different levels of coding required.
- Seller: you're a developer or vendor who wants to publish or distribute an agent. Cloud marketplaces and Hugging Face's Spaces both serve this function.
- Operator: you want agents already configured for a specific job, running on a schedule, with your approval before anything ships. A separate case-study collection of AI marketing agents reports one example where a seed-stage SaaS startup achieved 5x more content output with a two-person team after adopting this operating model.
Most growth and marketing teams fit the operator category, since the work they need (research, monitoring, content, reporting) is repeatable rather than a one-off build.
What to Verify Before Adopting a Marketplace Agent
Before adopting any agent from a marketplace, confirm what it accesses, how it's priced, and whether the vendor behind it is likely to still exist in a year.
Permissions scope: research on agent distribution channels found that 90% of deployed agents are over-permissioned, holding far more access than the task requires. Ask exactly what data and systems an agent can touch before approving it.
Pricing predictability: G2's analysis of AI agent-builder reviews found pricing concerns were the top complaint, ahead of steep learning curves. Confirm whether billing is seat-based, credit-based, or usage-based before signing.
Approval workflow: confirm the agent queues work for human sign-off rather than publishing or acting autonomously, especially for anything customer-facing.
Data residency: confirm where the agent's data and outputs are stored, particularly if it touches customer records or brand messaging.
Where Do Marketplace Agents Actually Run?
A marketplace is where you find and configure an agent; it is rarely where that agent runs persistently once deployed.
Most marketplace agents execute inside the buyer's own cloud account, a vendor-hosted workspace, or an orchestration layer that connects multiple tools together. This is why interoperability matters: CMSWire reports a forecast that by 2029, 40% of marketing technology vendors will support direct agent-to-agent interactions and API-based integrations, which would let agents sourced from different marketplaces work together rather than in isolation.
For a growth or marketing team, the practical question isn't just "which marketplace has the agent I need," but "where does that agent live once it's running, and what does it need access to in order to keep working."
Marketplace Choice vs Infrastructure Choice
Choosing a marketplace and choosing where agents run are two separate decisions, and conflating them is a common mistake.
A cloud-provider marketplace ties procurement to an existing account, but the agent itself may need its own credentials, data connections, and monitoring once live. An agent-building platform like MindStudio gives you a workflow, but you still decide where that workflow's outputs land, whether that's a CMS, a CRM, or a reporting dashboard. A growth platform like Mentionova runs its agents inside its own workspace and syncs outputs back into the tools a marketing team already uses, which removes a separate infrastructure decision for teams that don't want to manage one.
Before adopting an agent, map out who owns the runtime environment, who owns the data it touches, and who approves what it produces.
Operational Checklist for Persistent Agent Services
Once an agent is live, the work shifts from selection to maintenance.
- Review access on a schedule: re-check what each agent can read or write at least quarterly, not just at setup.
- Track output quality over time: compare what the agent produces this month against last month, not just against a one-time demo.
- Plan for deprecation: confirm what happens to historical data and workflows if the vendor changes pricing or sunsets a feature.
- Budget for usage spikes: if billing is usage-based, set alerts before a spike in agent activity turns into a surprise invoice.
- Keep a human in the approval loop: for any agent that touches customer communication or published content, require sign-off before anything ships.
Frequently Asked Questions
What is the difference between an AI agent marketplace and an AI agent directory?
A marketplace lets you configure, deploy, or transact for an agent inside the platform itself, while a directory typically only lists agents and links out to where they're hosted elsewhere. Cloud-provider catalogs and growth platforms with built-in agents are marketplaces; broad listing sites that just aggregate links function more like directories.
Is there a market for selling AI agents?
Yes. Cloud-provider marketplaces such as AWS Marketplace, Google Cloud Marketplace, and Microsoft's commercial marketplace, as well as open hubs like Hugging Face Spaces, all let developers publish and sell or distribute agents to buyers who can deploy them directly through those platforms.
Where can I sell my AI agent?
Developers typically publish agents through cloud-provider marketplaces such as AWS Marketplace, Google Cloud Marketplace, or Microsoft's commercial marketplace, or through open hubs such as Hugging Face's Spaces. Each path has different packaging and review requirements, so check the specific publisher program before building to a deadline.
How do I publish an AI agent to a marketplace?
Requirements vary by marketplace, but most require enrolling in a partner or publisher program, meeting the platform's technical and packaging requirements, and submitting the listing for review. Microsoft's commercial marketplace has publisher requirements that vary by offer type before an AI offer can go live.
Which AI agent marketplaces support MCP or agent interoperability?
Profound's agents can run inside Claude, Slack, or tools built on the Model Context Protocol (MCP), and broader interoperability support across martech vendors is expected to grow through the end of the decade. If interoperability is a priority, confirm whether a specific marketplace's agents can be called from outside its own platform before committing.
Can I deploy marketplace agents into my own infrastructure?
It depends on the marketplace. Hugging Face lets you deploy the same model on your own dedicated infrastructure or through its hosted inference service, while cloud-provider marketplaces typically keep the agent running inside that provider's account. Confirm this before adopting an agent if portability matters to your team.
Do AI agent marketplaces work with existing marketing tools like HubSpot or Google Analytics?
Integration depth varies significantly by platform. Some marketplaces offer no native connectors and require custom API work, while others include direct integrations with marketing stack tools. Mentionova, for example, connects to Search Console, GA4, HubSpot, Notion, Webflow, and G2 reviews on every plan without a separate enterprise contract.
What is the best AI agent on the market right now?
There is no single best AI agent. The right choice depends on whether a team needs research, monitoring, content, or customer-support automation, and no platform in this comparison wins across every category. For growth and marketing teams specifically, Mentionova's 100+ growth agents are scoped to research, monitoring, content, and reporting tasks, with a one-click human approval step before anything ships.
Are AI agent marketplaces safe to use for marketing teams?
Safety depends on permissions scope and workflow design, not the marketplace itself. Research on agent distribution channels found 90% of deployed agents are over-permissioned. Before adopting any agent, confirm exactly what data and systems it can access, require human approval before customer-facing outputs ship, and verify where the agent's data and outputs are stored.
Choosing the Right AI Agent Marketplace for Your Team
Choosing an AI agent marketplace is really two decisions: which catalog or platform to shop from, and what kind of ongoing oversight you're prepared to run once an agent is live. For growth and marketing teams specifically, that second decision tends to matter more, since the work (research, monitoring, content, reporting) repeats every week rather than running once. See how it works with Mentionova's six-engine visibility tracking and 100+ growth agents before deciding how much of that repeat work to automate.