Skip to content
Alternatives
Software like Agentuity
What else does this job. Matched on what each project does, not on who links to whom.
Closest first
- Agentryagentry.comAgentry provides identity, discovery, orchestration, reputation, wallets, and escrow payments for AI agents. Its API supports agent registration and invocation, with Nostr-native identity and Bitcoin or Lightning settlement for developers building agent commerce systems.
- Agentcygoagentcy.comAgentcy is a hosted AI agent for marketers that connects to various marketing data sources and provides actionable insights. It integrates with tools like Claude, ChatGPT, and others, streamlining analytics and reporting for marketing teams.
- AI Agentaiagent.appAI Agent provides a no-code platform for creating and deploying autonomous AI agents that handle complex tasks such as research, report generation, and workflow automation. Agents can connect to tools like GitHub, Gmail, Notion, and Linear, use company documents for context, plan multi-step processes, and execute actions with minimal human oversight. It enables teams to multiply productivity by delegating routine work to intelligent software agents.
- Agentlyagently.techAgently is an open-source Python framework that enables enterprises to build, deploy, and monitor AI agent systems with structured outputs, external integrations, and process orchestration. It supports multiple AI providers and is designed for enterprise AI developers.
- Agntableagntable.comAgntable is a fully managed AI hosting platform that enables users to deploy open-source AI agents with one click. It offers built-in security, auto-scaling, and CLI support, making it accessible for both non-technical users and technical teams who want to avoid infrastructure management.
- Agent-Nativeagent-native.comAgent-Native is an open-source framework for agentic apps. It is described as a way to build applications with agents at the core, so developers do not have to choose between apps and agents; the site says Agent-Native apps are both. The framework is presented for building SaaS tools, internal tools, and other agent-first applications. A central feature is its action model: one operation can become a UI action, an agent tool, an HTTP endpoint, an MCP/A2A surface, a CLI command, a scoped permission check, and an audit trail. The documentation and examples also mention notifications, recurring jobs, agent teams, monorepos, permissions and RBAC, organizations, workspace secrets, docs search, source search, context awareness, observability, real-time sync, SQL state, multi-tenancy, data loaders, live queries, agent instructions, provider grants, comments, review links, privacy controls, skills, security, audit logs, workspaces, voice input, generative UI, tool calls, shared actions, i18n, MCP auth, external agents, A2A handoffs, human handoff, durable resume, sharing and privacy, real-time collaboration, SSO, OAuth, MCP servers, scoped access, DB adapters, approvals, automations, governance, jobs, AG-UI dispatch, background runs, rate limits, queues, cron schedules, analytics, experiments, feedback loops, file uploads, evals, app skills, provider APIs, app web surfaces, one-click forks, local file mode, memory, webhooks, self-editing code, schema migrations, hosted deploys, environment setup, OAuth callbacks, exports, and dashboards. The site includes several example apps built with the framework, including Clips, a Loom-like app with browser debug capture, calendar-synced meeting notes, voice dictation, transcription, summarization, search, and agent editing; a visual plan mode for Codex, Claude Code, and coding agents; a design studio for Figma-style prototyping; a Markdown and MDX content app for local files; a Slides app for generating presentations from prompts; an analytics app that connects to any data source and lets the agent write SQL and generate visualizations; and a minimal ChatGPT-style app. The framework can be used from its docs or through Builder.io, and the page shows an npx create command for starting a new app. It also links to GitHub, Discord, npm, and a docs search interface. The site describes the framework as open source, forkable, and yours.
- HeyAgentheyagent.liveHeyAgent is a web-based platform that enables users to create and deploy autonomous AI proxy agents for networking and outreach. The agents autonomously interact with others, evaluate synergies, and provide daily briefings to users.
- AGENTISagentisexchange.comAGENTIS is an infrastructure platform for AI agent commerce. Its homepage describes it as providing escrow, reputation, and dispute resolution for the autonomous economy, with a central theme of giving an AI agent a wallet, a marketplace, and a reputation. The platform includes an agent directory, block explorer, oversight dashboard, agent evaluations, a vault dashboard, guild workspace, and futures trading. It also offers developer tooling through a Python SDK, quickstart guide, API documentation, API playground, no-code builder, agent templates, and a builder directory. The site says agents can register with one API call, receive an instant API key, build a profile with skills, portfolio, and gig packages, earn verified badges, and then engage and deliver work while building reputation. It also states that operators can submit details about an AI fleet, complete personal onboarding and identity verification, and manage all agents from a single operator dashboard. AGENTIS also advertises persistent, cross-machine memory, shown in a Python example that includes memory_write, and says it supports REST and MCP integration. The page lists 400+ API endpoints, 23 MCP tools, and integrations with Claude, GPT-4, Gemini, and Cursor. It also mentions a live dashboard, live metrics, and a review process for operators intended to protect counterparties and maintain platform integrity. The platform is described as live since 15 March 2026 and as SA-based and POPIA-compliant. Pricing is split between free access for agents and subscription tiers for operators. Listed operator tiers include Explorer Free, Builder R299 per month, Professional R999 per month, and Enterprise R2,499 per month, with varying agent registrations, transaction limits, vault storage, commission rates, and support levels. Agent subscriptions are also offered, including AgentHub Basic Free and AgentHub Pro at R36 per month. Additional paid storage tiers and add-ons are listed, and the pricing section states that all paid tiers offer a 20% discount for annual prepayment. The page also says 10% of all platform commission is allocated to a charitable fund.
- Agentendagentend.aiAgentend is a Python framework for building agent as a backend systems, where the agent handles the application’s backend role rather than relying on traditional routes, controllers, and related infrastructure. It is aimed at agent-powered products and supports code-defined capabilities instead of endpoint-based design. The framework’s documented flow starts with a user intent, described as natural language rather than a structured API call. A kernel classifies and routes the intent, with the page describing this step as using a small model with under 10 ms latency. It then hydrates memory through a context bus with five tiers of progressive loading, and workers execute tasks while events stream in real time through the AG-UI protocol. The same page also highlights typed worker slots, DAG workflows with parallel steps and human-in-the-loop interrupts, a dual-layer semantic cache based on hash and vector similarity, PALADIN injection defense, per-tenant token budget enforcement, eight hook points with YAML manifests, and pip-installable extensions. Agentend includes a chat-to-build interface for creating capabilities without code, and the example on the site shows a capability defined in Python with a decorator, worker names, domain context, and a tool function. The architecture section names AG-UI, MCP, and A2A as part of a “protocol triangle,” and the observability and persistence notes mention OpenTelemetry traces and metrics, plus SQLAlchemy 2.0 async with multi-tenant row-level security. Installation commands shown on the page use pip and a local serve workflow, and the code sample imports Agentend, Capability, and tool from the package. The site describes the project as production-ready and says it is licensed under AGPL-3.0-or-later. It also names Cloud, Documentation, Quickstart, Fleet, Memory, Events, and Community in its navigation, and the page title identifies it as a Python framework.
- Agenitiageniti.devAgeniti is a developer framework designed for building applications whose capabilities can be exposed as structured actions across multiple environments. Its core model centers on defining actions as the primary unit of agentic capability, allowing developers to create a single action contract and then generate adapters for various surfaces, including CLI, HTTP, MCP (Machine Control Protocol), OpenAI and AI SDK tools, React hooks, and typed clients. This approach enables the same application logic to be accessed and operated by agents, operators, or automation systems without duplicating definitions for each interface. The framework provides a runtime that handles critical production concerns such as validation, permissions, retries with per-attempt cancellation, idempotency, concurrency limits, secret redaction, and detailed error codes. Ageniti supports streaming events as a primitive, so logs, progress updates, and artifacts can be emitted live and subscribed to by any consumer, such as user interfaces, agent loops, or log shippers. Integration is facilitated through practical starter patterns and recipes, making it easier to wire application features to different surfaces like CLI, MCP servers, React apps, and automation scripts. Ageniti is unopinionated about higher-level orchestration, leaving decisions about prompt orchestration, tool selection, and workflow composition to the developer. It focuses on providing the action contract and runtime, while orchestration, memory management, and workflow composition remain outside its scope. Developers can bring their own schema validation libraries, including Zod, Valibot, ArkType, or any library implementing Standard Schema v1, ensuring compatibility with existing typed validation. The framework is delivered as the @ageniti/core package via npm, and is built on technologies such as React, TypeScript, Node.js, and Next.js. Documentation, templates, and a GitHub repository are available to support integration and onboarding. Ageniti is intended for developers seeking to expose application capabilities to agents and automation tools through explicit, reviewable contracts and reusable product capabilities.
- Agentationagentation.comAgentation is a desktop-only tool designed to facilitate visual feedback for AI coding agents. Its primary function is to allow users to annotate user interfaces by clicking on elements, adding notes, and generating structured context that can be understood and acted upon by AI tools. Users interact with Agentation by activating an interface element, hovering to highlight UI components, and attaching annotations with specific feedback. The tool then formats this information into markdown, which can be copied and pasted into AI agents such as Claude Code, Codex, or other compatible tools. The structured output provided by Agentation includes CSS selectors for identifying elements in the codebase, source file paths for direct navigation to relevant lines, the React component tree to give context about UI hierarchy, computed styles to convey the current appearance, and the user's feedback with intent and priority. This approach streamlines the process of communicating UI feedback to AI agents, reducing the need for manual, textual descriptions of interface elements. Agentation also offers integration with MCP API and webhooks, enabling some agents to access annotations directly without requiring manual copy-paste. When integrated with MCP, agents can immediately interpret pointed feedback and respond to specific annotations as directed by the user. The tool is positioned for users working with AI coding agents, particularly in environments where agents have access to the codebase and can act on structured UI feedback. There is no information in the provided evidence regarding pricing or licensing details.
- AgentVoyagentvoy.comAgentVoy is a platform for developing, deploying, and managing AI agent applications that supports both single-agent and multi-agent pipelines. It is designed for users who want to build agentic apps using a variety of popular frameworks and models, providing a unified workflow from project creation to deployment. The tool emphasizes rapid project setup, real-time development insights, and consistent security guardrails across different agent frameworks. Developers can use AgentVoy’s command-line interface to create new projects with a single command, selecting from seven supported frameworks, including OpenAI Agents SDK, Google ADK, CrewAI, LangGraph, Anthropic SDK, LlamaIndex, and AutoGen—all using Python. For model integration, the platform accommodates a wide range of providers such as OpenAI, Anthropic, Google, Groq, Mistral, and also allows fully local model execution with Ollama. The Streamlit-based chat UI auto-detects available models from environment variables, enabling dynamic model switching without restarting the application. Multi-agent pipelines are supported, allowing sequential workflows where each agent builds upon the previous stage, with real-time visualization of pipeline stages. A central feature of AgentVoy is its real-time DevTools dashboard, accessible via a web interface. This dashboard provides live tracing of agent operations, including LLM calls, tool invocations, guard checks, and pipeline stages, with trace events streamed over WebSocket. Projects include a FastAPI server, Streamlit chat UI, and cloud configuration files, facilitating both local experimentation and full-scale deployment. Deployment is streamlined with one-command options to Docker, Fly.io, Railway, Google Cloud Platform (Cloud Run), and AWS Lambda, with automatic handling of secrets, configuration, and health checks. The platform can also add deployment capabilities to existing agent projects without altering core agent logic. Security and operational guardrails are built into every AgentVoy project via a universal agent.guard.yml configuration file. This file enforces permissions, cost limits, iteration caps, prompt injection blocking, and PII detection at runtime, and its settings are automatically integrated into deployment infrastructure. No installation is required to get started; projects can be created and deployed directly using npx commands. AgentVoy is intended for developers seeking a unified, secure, and efficient approach to building and shipping AI agent applications across multiple frameworks and deployment targets.
Ranked by how close each one sits to Agentuity in the index, not by popularity. Back to Agentuity →