Autonomous agent platform for task-driven chatbots & agents
AgentGPT is an open-ended autonomous agent builder that lets users spin up multi-step AI agents to complete tasks using LLMs, aimed at makers and small teams who need automated workflows; its free tier is usable for experimentation while paid monthly plans unlock higher API usage and more concurrent agents.
AgentGPT is an autonomous agent platform that creates chatbots and multi-step agents which can plan and execute tasks using LLMs. The platform's primary capability is turning objectives into action plans executed by chains of prompts and tools, with a focus on persistent, goal-directed agents. Its key differentiator is a lightweight, web-based UI that exposes agent memory, tools, and step-by-step run logs to non-engineers. AgentGPT serves developers, product managers, and growth teams testing automation; pricing includes a free tier for experimentation and paid tiers for higher API usage and concurrency.
AgentGPT launched as a public-facing platform that enables users to create autonomous agents—mini programs powered by large language models that take a user objective and break it into actionable steps. Originating as a community-driven project and iterating rapidly, AgentGPT positions itself between single-turn chatbots and full orchestration platforms by providing a simple web console, agent templates, and built-in memory. The core value proposition is lowering the barrier to building multi-step, goal-oriented agents without writing orchestration code, offering visible step logs and agent state for transparency.
Key features center on agent creation, tool integrations, and run-time observability. The agent builder lets you define an objective, role, and available tools, then select which LLM to use (OpenAI API models are supported). Agents can persist short-term memory to improve follow-up behavior, call external tools (like web search and URL fetch), and save session transcripts. The run console shows a step-by-step plan with subtask outputs and token usage per step, allowing users to stop, restart, or edit the plan mid-run. Templates and community-shared agents speed setup for common workflows like research, outreach drafting, and data extraction.
AgentGPT’s pricing mixes a free tier and paid subscription options. The free tier allows limited agent runs and community access but restricts concurrency and API token usage; it’s intended for testing only. Paid tiers (as listed on the site) add monthly API credit or enable linking to your own OpenAI key for consumption-based billing, increase concurrent agents, and unlock team features and private agents. Enterprise or custom plans are available for higher throughput and SSO. Exact monthly prices and credits have changed over time; users should check the site for the current numeric plan details and whether you pay for hosted API usage or supply your own key.
Real-world users include marketers and engineers who need lightweight automation without building an orchestration layer. A growth marketer uses AgentGPT to automate outreach message drafts and A/B test variants across 100 leads per week, and a data analyst uses agents to scrape and summarize 50 competitor pages for weekly reports. Product managers prototype multi-step user flows with agents to validate automation ideas before engineering investment. Compared to full-featured orchestration platforms like LangChain-based self-hosted stacks, AgentGPT trades deep customization for a faster web-first experience and clearer step logs.
Three capabilities that set AgentGPT apart from its nearest competitors.
Current tiers and what you get at each price point. Verified against the vendor's pricing page.
| Plan | Price | What you get | Best for |
|---|---|---|---|
| Free | Free | Limited agent runs, community templates, low concurrency | Experimenters testing basic agents |
| Pro / Plus | Exact monthly pricing varies (check site) | Higher monthly API credit or ability to link your own OpenAI key, more concurrency | Individual creators building regular agents |
| Team | Exact monthly pricing varies (check site) | Shared team agents, additional API credits, private agents | Small teams coordinating agent workflows |
| Enterprise | Custom | Custom throughput, SSO, priority support | Organizations needing scale and compliance |
Copy these into AgentGPT as-is. Each targets a different high-value workflow.
Role: You are a senior growth copywriter. Task: produce 5 cold outreach email variants for a B2B SaaS product. Constraints: each email must be <=120 words, use a different tone (friendly, urgent, data-driven, concise, curious), include a subject line and a one-line CTA, avoid jargon, and personalize with {{first_name}} and {{company}} tokens. Output format: JSON array of 5 objects with fields {"tone","subject","body","cta"}. Example element: {"tone":"friendly","subject":"Quick question, {{first_name}}?","body":"...","cta":"Are you open to 15 minutes next week?"}. Do not include analysis or extra text.
Role: You are a concise market researcher. Task: read the provided competitor webpage content and produce a one-paragraph summary plus three bullet key insights. Constraints: summary must be <=80 words; bullets must be single-line, actionable, and mention CTA, pricing signals, and unique value proposition if present. Output format: JSON object {"summary":"...","insights":["...","...","..."]}. Example: {"summary":"...","insights":["CTA: free trial","Pricing: tiered","UVP: no-code connector"]}. Return only the JSON object; do not include source links or commentary.
Role: You are a competitive analyst automating page summaries. Input variable: replaceable array of URLs or page texts. Constraints: for each page produce (1) one-sentence elevator summary, (2) top 3 product/feature takeaways, (3) primary CTA text, (4) inferred pricing model (free/trial/subscription/enterprise/unknown), (5) sentiment score -1..+1. Output format: JSON array of objects {"url","summary","takeaways":[...],"cta","pricing","sentiment"}. Example object: {"url":"...","summary":"...","takeaways":["...","...","..."],"cta":"Try free","pricing":"trial","sentiment":0.3}. Return only JSON.
Role: You are a product manager prototyping a signup flow for a web app. Constraints: produce exactly 5 steps (discovery to first success), include for each step: "name", "goal", "UI elements", "API endpoint (method + path)", "request example", "response example", and 1 acceptance criterion. Also list 3 common error cases with suggested UI messages. Output format: JSON object {"steps":[...],"errors":[...]} with examples. Example step: {"name":"Email capture","goal":"Collect email","UI elements":"input, continue button","api":"POST /api/signup","request":"{email} ","response":"{userId}","acceptance":"Email validated and stored"}. Return only JSON.
Role: You are a growth automation architect designing an autonomous agent to run weekly A/B tests of outreach variants. Multi-step requirements: 1) generate 100 outreach variants using templated tokens, 2) dispatch variants across channels with rate limits, 3) collect opens/replies, 4) calculate statistical significance and select winners, 5) update memory and retire losers. Constraints: include memory schema, tool list (email API, scheduler, tracker), evaluation metrics (lift, p-value threshold 0.05), roll-forward rules, and monitoring alerts. Output format: detailed JSON plan with keys {"schedule","memory_schema","tools","variant_generation_prompt","evaluation","runbook"}. Example variants snippet and a sample evaluation calculation are required. Return only JSON.
Role: You are a data engineer creating an autonomous agent to scrape up to 50 pages weekly, extract structured records, deduplicate, store in a relational DB, and produce weekly summary reports. Multi-step: crawling, parsing, schema mapping, dedupe logic, storage, reporting, monitoring. Constraints: include retry/backoff, politeness (rate limit and robots), incremental updates, and error handling. Output format: JSON with keys {"crawl_strategy","parsers","dedupe_rules","db_schema_sql","ingest_api","logging_schema","alerts","report_template"}. Provide an example SQL table definition and one sample parsed record. Return only JSON.
Choose AgentGPT over AutoGPT if you want a web UI with editable step logs and easier templates rather than code-first orchestration.
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