Overview
Agentplace is a no-code platform for building, deploying, and managing AI agents that work like autonomous teammates across your business. Rather than coding an agent from scratch or wiring together fragile API chains, you use Agentplace's visual builder to define what an agent knows, which tools it can call, and when to loop in a human — then deploy it instantly to the cloud and access it through Agentplace's work environment, including voice interactions, with public, private, or restricted sharing.
The platform runs on an AI-native architecture where every agent has persistent memory through a Skills system and can connect to external services via Model Context Protocol (MCP). Agentplace showcases use cases across customer support, operations, HR, research, and finance — handling repetitive, judgment-heavy workflows with agents that stay on-brand, stay auditable, and hand off to humans exactly when they should.
With a free tier that includes 1,000 agent calls per month and the full builder toolset, Agentplace is accessible to solo builders and small teams before they need to commit to a paid plan.
Key Features
No-code agent builder with instant cloud deployment — Design agents visually without writing backend code. Once configured, Agentplace deploys your agent to the cloud immediately — no infrastructure provisioning, no DevOps work required.
Skills and MCP integrations — Extend agents with Skills that give them persistent memory and domain knowledge, or connect them to external tools and data sources via the Model Context Protocol. Agents remember context across sessions and interact with your existing stack.
Multi-model support with BYOK — Run agents on OpenAI, Anthropic, or Google Gemini models out of the box. If you have your own API keys, Agentplace supports bring-your-own-key (BYOK) so you stay in control of costs and model selection.
Multi-runtime deployment — Build once, deploy instantly to Agentplace's cloud, and work with the agent in a ChatGPT-style environment that includes voice interactions. Agents can be shared as public, private, or restricted.
Human-in-the-loop approvals — Agents surface a custom UI panel whenever an action requires human review or sign-off. Sensitive operations stay under human control while automation handles everything else, keeping your workflows compliant and auditable.
GitHub integration and automated testing — Connect GitHub to the builder so it can read your codebase and documentation context while helping you configure agents.
How to Get Started
Getting your first agent running on Agentplace takes a few steps:
- Sign up for a free account — Visit agentplace.io and create your account. The Free plan gives you immediate access to the full builder and 1,000 agent calls per month.
- Create a new agent — In the builder, define your agent's purpose, name, and persona. Describe what it should do and what it should never do.
- Add Skills and connect integrations — Attach Skills to give your agent persistent memory or domain knowledge. Connect MCP integrations to external tools, APIs, or databases your agent needs to access.
- Select your AI model — Choose from OpenAI, Anthropic, or Gemini models, or add your own API key under BYOK settings.
- Connect GitHub (optional) — Link GitHub so the builder can read your codebase and documentation context while helping you configure the agent.
- Set access controls and deploy — Choose whether your agent is Private (you only), Restricted (invite only), or Public (anyone with the link), then deploy. Your agent goes live instantly.
After deployment, monitor call usage in your dashboard and add human-approval checkpoints to any sensitive actions before expanding to more users.
Pricing & Plans
Agentplace offers three tiers, with the free plan covering the full builder and a generous call allowance for getting started:
| Plan | Price | Agent Calls | Highlights |
|---|---|---|---|
| Free | $0/month | 1,000/month | Full builder, MCP integrations, all three AI model providers, GitHub Connect |
| Pro | $29/month | 2,000–50,000/month | Scalable call tiers (2k, 5k, 10k, 20k, 50k), all Free features |
| Business | Custom | Custom | SSO, private cloud, enhanced security controls, custom integrations, dedicated support |
The Pro plan's call volume is flexible — you pick the tier that matches your usage rather than paying for a fixed ceiling. The public pricing page currently shows Pro as billed monthly; annual pricing is not listed.
Best For
- Solo developers and indie hackers who want to ship AI-powered workflows without setting up backend infrastructure
- Small operations or customer support teams that need task-specific agents deployable in days, not months
- Product managers who want to prototype AI agent workflows before involving engineering resources
- Businesses that require human approval gates in their automation, such as finance approvals or HR workflows
- Teams already using MCP-compatible tools who want a no-code layer to orchestrate agents on top of their existing stack
FAQ
What is Agentplace?
Agentplace is a no-code platform for building and deploying AI agents. You configure an agent's behavior, tools, and memory in a visual builder, then deploy it instantly as a web app, voice interface, CLI tool, or sub-agent — without writing server-side code.
Is there a free plan?
Yes. The Free plan is available at $0/month and includes access to the full agent builder, 1,000 agent calls per month, MCP integrations, all three built-in AI model providers (OpenAI, Anthropic, Gemini), and GitHub Connect.
What does "agent call" mean?
An agent call is a single invocation of your agent — for example, a user sending a message and receiving a response. An agent call is a usage unit counted against your monthly plan allowance. The public pricing page lists how many agent calls are included in each plan, but does not currently provide a more detailed public definition.
What AI models can I use?
Agentplace comes with OpenAI, Anthropic (Claude), and Google Gemini models built in. You can also bring your own API keys (BYOK) to use these models under your own accounts, giving you full control over billing and model versions.
What are Skills and how do they work?
Skills are modular capabilities you attach to an agent to give it persistent memory, domain knowledge, or access to specific data. Skills are self-contained knowledge modules the agent loads when relevant. They provide reusable domain knowledge and procedures, while Agentplace also describes the file system as part of the agent's memory layer.
What is MCP and why does it matter?
MCP (Model Context Protocol) is an open standard for connecting AI agents to external tools, APIs, and data sources in a structured way. Agentplace supports MCP integrations, which means your agents can connect to any MCP-compatible service — and as the protocol gains wider adoption, your integration library grows automatically.
Can I run the same agent in multiple environments?
Yes. Deploy a single agent to Agentplace's cloud, work with it in a voice-enabled environment, and share it as public, private, or restricted access — all without rebuilding the logic for each context.
How does the human-in-the-loop feature work?
When you configure an agent, you can mark specific actions as requiring human approval. At runtime, the agent pauses at those steps and surfaces a custom UI panel for a human reviewer to approve or reject before proceeding. This keeps sensitive or high-stakes decisions under human control.
Is Agentplace suitable for enterprise use?
The Business plan is designed for enterprise requirements, including SSO, private cloud deployments, enhanced security controls, custom integrations, and dedicated support. Contact Agentplace directly for Business plan pricing and deployment options.
How is Agentplace different from tools like n8n or Make?
n8n and Make are workflow automation platforms built around trigger-and-action pipelines. Dedicated AI agent runners like MuleRun focus on always-on execution. Agentplace focuses on AI agents with skills, MCP integrations, human review, and voice-enabled work environments — not just execute fixed sequences. Agents on Agentplace can handle ambiguity, loop in humans when needed, and operate across voice, web, and CLI runtimes from a single configuration.
