Alternatives to Deep Agents
Compare Deep Agents alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Deep Agents in 2026. Compare features, ratings, user reviews, pricing, and more from Deep Agents competitors and alternatives in order to make an informed decision for your business.
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1
Claude Code
Anthropic
Claude Code is an AI-powered coding agent designed to work directly inside your existing development environment. It goes beyond simple autocomplete by understanding entire codebases and helping developers build, debug, refactor, and ship features faster. Developers can interact with Claude Code from the terminal, IDEs, Slack, or the web, making it easy to stay in flow without switching tools. By describing tasks in natural language, users can let Claude handle code exploration, modifications, and explanations. Claude Code can analyze project structure, dependencies, and architecture to onboard developers quickly. It integrates with common command-line tools, version control systems, and testing workflows. This makes it a powerful companion for both individual developers and teams working on complex software projects.Starting Price: $20/month -
2
Hermes Agent
Nous Research
Hermes Agent by Nous Research is an open-source autonomous AI agent designed to run locally on your server and improve over time. It operates independently from traditional chatbots by maintaining persistent memory and learning from past interactions. The agent can integrate with multiple platforms such as Slack, Discord, Telegram, and WhatsApp through a unified gateway. Hermes supports automation tasks like scheduling reports, managing workflows, and executing commands using natural language. It also enables parallel task execution through subagents, improving efficiency for complex operations. With built-in tools for web browsing, search, and code execution, it provides a versatile environment for various tasks. Overall, Hermes Agent acts as a continuously evolving AI system that adapts to user needs and workflows.Starting Price: $20/month -
3
Muse Code
Meta
Muse Code is Meta’s terminal coding agent, powered by Muse Spark 1.2, for handling complex software engineering tasks across large repositories. The agent can plan changes, write code, validate results, and coordinate multiple persistent subagents during development sessions. Muse Code uses async background agents that stay active throughout a session to reduce repeated information gathering and help complete multi-step tasks with less steering. Its runtime uses a local event log that records model calls, tool runs, approvals, and edits so sessions can be replayed and resumed after failures. Muse Code includes bundled skills such as /plan for approval-gated planning, /grill for stress-testing plans, and /goal for working toward completion. Built for AI developers and software teams, Muse Code helps automate coding workflows, long-running engineering tasks, debugging, and repository-level development.Starting Price: $1.25 per 1M tokens (input) -
4
Claude Agent SDK
Claude
The Claude Agent SDK is a developer toolkit that enables the creation of autonomous AI agents powered by Claude, allowing them to perform real-world tasks beyond simple text generation by interacting directly with files, systems, and tools. It provides the same underlying infrastructure used by Claude Code, including an agent loop, context management, and built-in tool execution, and is available for use in Python and TypeScript. With this SDK, developers can build agents that read and write files, execute shell commands, search the web, edit code, and automate complex workflows without needing to implement these capabilities from scratch. It maintains persistent context and state across interactions, enabling agents to operate continuously, reason through multi-step problems, take actions, verify results, and iterate until tasks are completed.Starting Price: Free -
5
LangChain
LangChain
LangChain is a powerful, composable framework designed for building, running, and managing applications powered by large language models (LLMs). It offers an array of tools for creating context-aware, reasoning applications, allowing businesses to leverage their own data and APIs to enhance functionality. LangChain’s suite includes LangGraph for orchestrating agent-driven workflows, and LangSmith for agent observability and performance management. Whether you're building prototypes or scaling full applications, LangChain offers the flexibility and tools needed to optimize the LLM lifecycle, with seamless integrations and fault-tolerant scalability. -
6
LangGraph
LangChain
Gain precision and control with LangGraph to build agents that reliably handle complex tasks. Build and scale agentic applications with LangGraph Platform. LangGraph's flexible framework supports diverse control flows – single agent, multi-agent, hierarchical, sequential – and robustly handles realistic, complex scenarios. Ensure reliability with easy-to-add moderation and quality loops that prevent agents from veering off course. Use LangGraph Platform to templatize your cognitive architecture so that tools, prompts, and models are easily configurable with LangGraph Platform Assistants. With built-in statefulness, LangGraph agents seamlessly collaborate with humans by writing drafts for review and awaiting approval before acting. Easily inspect the agent’s actions and "time-travel" to roll back and take a different action to correct course.Starting Price: Free -
7
PydanticAI
Pydantic
PydanticAI is a Python-based agent framework designed to simplify the development of production-grade applications using generative AI. Built by the team behind Pydantic, the framework integrates seamlessly with popular AI models such as OpenAI, Anthropic, Gemini, and others. It offers type-safe design, real-time debugging, and performance monitoring through Pydantic Logfire. PydanticAI also provides structured responses by leveraging Pydantic to validate model outputs, ensuring consistency. The framework includes a dependency injection system to support iterative development and testing, as well as the ability to stream LLM outputs for rapid validation. It is ideal for AI-driven projects that require flexible and efficient agent composition using standard Python best practices. We built PydanticAI with one simple aim: to bring that FastAPI feeling to GenAI app development.Starting Price: Free -
8
Pi Agent
Pi
Pi is a minimal terminal coding harness built to adapt to developer workflows instead of forcing developers to adapt to it. It ships with powerful defaults, but stays intentionally small and aggressively extensible, letting users customize Pi with extensions, skills, prompt templates, themes, and shareable packages from npm or git. If a team needs a command, tool, provider, workflow, or UI tweak, they can ask Pi to build it, manipulate it in place, reload, and keep going. Pi supports interactive, print/JSON, RPC, and SDK modes, making it usable as a full terminal UI, a scriptable command, a JSON event stream, or an embeddable agent harness. It works with 15+ providers and hundreds of models, including Anthropic, OpenAI, Google, Azure, Bedrock, Mistral, Groq, Cerebras, xAI, Hugging Face, Kimi For Coding, MiniMax, OpenRouter, Ollama, and more, with mid-session model switching.Starting Price: Free -
9
OpenCode
Anomaly Innovations
OpenCode is the AI coding agent purpose-built for the terminal. It delivers a responsive, themeable terminal UI that feels native while streamlining your workflow. With LSP auto-loading, it ensures the right language servers are always available for accurate, context-aware coding support. Developers can spin up multiple AI agents in parallel sessions on the same project, maximizing productivity. Shareable links make it easy to reference, debug, or collaborate across sessions. Supporting Claude Pro and 75+ LLM providers via Models.dev, OpenCode gives you full freedom to choose your coding companion.Starting Price: Free -
10
dcode
LangChain
dcode is an open-source terminal coding agent for developers and software teams. Built on the Deep Agents SDK, it can plan and execute coding tasks, inspect and edit project files, run tools, and delegate work to subagents. Its interactive terminal interface streams responses and lets users resume conversations across sessions; headless mode supports scripted and CI workflows. Users select a compatible model provider and supply their own credentials, then customize models, tools, plugins, skills, memory, middleware, hooks, and approval rules. Tool calls can be approved or rejected, and code can run locally or in supported remote sandboxes. dcode supports MCP tools and can connect to LangSmith for tracing prompts, responses, tool calls, errors, and token usage. It is intended for developers who want to configure and inspect an AI coding agent rather than use a fixed coding assistant.Starting Price: Free -
11
Agno
Agno
Agno is a lightweight framework for building agents with memory, knowledge, tools, and reasoning. Developers use Agno to build reasoning agents, multimodal agents, teams of agents, and agentic workflows. Agno also provides a beautiful UI to chat with agents and tools to monitor and evaluate their performance. It is model-agnostic, providing a unified interface to over 23 model providers, with no lock-in. Agents instantiate in approximately 2μs on average (10,000x faster than LangGraph) and use about 3.75KiB memory on average (50x less than LangGraph). Agno supports reasoning as a first-class citizen, allowing agents to "think" and "analyze" using reasoning models, ReasoningTools, or a custom CoT+Tool-use approach. Agents are natively multimodal and capable of processing text, image, audio, and video inputs and outputs. The framework offers an advanced multi-agent architecture with three modes, route, collaborate, and coordinate.Starting Price: Free -
12
LangSmith
LangChain
Unexpected results happen all the time. With full visibility into the entire chain sequence of calls, you can spot the source of errors and surprises in real time with surgical precision. Software engineering relies on unit testing to build performant, production-ready applications. LangSmith provides that same functionality for LLM applications. Spin up test datasets, run your applications over them, and inspect results without having to leave LangSmith. LangSmith enables mission-critical observability with only a few lines of code. LangSmith is designed to help developers harness the power–and wrangle the complexity–of LLMs. We’re not only building tools. We’re establishing best practices you can rely on. Build and deploy LLM applications with confidence. Application-level usage stats. Feedback collection. Filter traces, cost and performance measurement. Dataset curation, compare chain performance, AI-assisted evaluation, and embrace best practices. -
13
AgentSea
AgentSea
AgentSea is an open source platform designed to build, deploy, and share AI agents with ease. It delivers a collection of libraries and tools for building AI agent apps, favoring the UNIX philosophy of doing one thing well. Tools can be used individually or stacked together into a single agent app, and are compatible with frameworks like LlamaIndex and LangChain. Key components include SurfKit, a Kubernetes-style orchestrator for agents; DeviceBay, offering pluggable devices like file systems and desktops; ToolFuse, a library that wraps scripts, third-party apps, and APIs as Tool implementations; AgentD, a daemon making a Linux desktop OS accessible to bots; AgentDesk, a library for running AgentD-powered VMs; Taskara, for task management; ThreadMem, for building multi-role persistent threads; and MLLM, simplifying communication with multiple LLMs and multimodal LLMs. AgentSea also offers alpha agents like SurfPizza and SurfSlicer, which navigate GUIs using multimodal approaches.Starting Price: Free -
14
Microsoft Agent Framework
Microsoft
Microsoft Agent Framework is an open source SDK and runtime designed to help developers build, orchestrate, and deploy AI agents and multi-agent workflows using languages such as .NET and Python. It combines the simple agent abstractions of AutoGen with the enterprise-grade capabilities of Semantic Kernel, including session-based state management, type safety, middleware, telemetry, and broad model and embedding support, creating a unified platform for both experimentation and production use. It introduces graph-based workflows that give developers explicit control over how multiple agents interact, execute tasks, and coordinate complex processes, enabling structured orchestration across sequential, concurrent, or branching scenarios. It supports long-running and human-in-the-loop workflows through robust state management, allowing agents to maintain context, reason through multi-step problems, and operate continuously over time.Starting Price: Free -
15
Netra
Netra
AI agents fail silently in production. Wrong answers, broken loops, cost spikes, behavior drift after a prompt change, and no stack trace to explain why. Netra is the single platform to trace, evaluate, simulate and security test your agents. Built for text, voice, image and video agents. SOC2 Type II certified. GDPR and HIPAA compliant. US and EU data residency. Integrates with: LangChain, LangGraph, CrewAI, LlamaIndex, OpenAI, Anthropic, Gemini, AWS Bedrock, and 30+ more.Starting Price: $39/month -
16
Cua
Cua
Cua is a computer-use agent platform that lets AI agents see screens, click buttons, type, and run code just like a human across macOS, Windows, Linux, browsers, and mobile environments. It provides cloud-based, sandboxed desktops where agents can automate real software workflows without relying on APIs. Built on open-source Cua agents, the platform enables developers to build, run, and scale computer-use agents with precision and reliability. Cua supports multi-step tasks, structured outputs, and human-in-the-loop recovery for complex automation. Agents operate in fully isolated environments to ensure safety and reproducibility. Cua is designed to make AI interaction with real applications practical and scalable.Starting Price: $10/month -
17
Superpowers
Superpowers
Superpowers is an open-source software development methodology and skills framework designed to improve how coding agents plan, build, test, and review software. The project gives AI coding tools a structured workflow that helps them clarify requirements before writing code. It supports agents such as Claude Code, Codex CLI, Codex App, Factory Droid, Gemini CLI, OpenCode, Cursor, and GitHub Copilot CLI. Superpowers guides agents through brainstorming, design approval, implementation planning, test-driven development, subagent-driven execution, code review, and branch completion. Its skills library emphasizes red-green-refactor testing, systematic debugging, isolated git worktrees, verification, and evidence-based completion. Superpowers helps developers turn AI coding agents into more disciplined engineering partners that follow repeatable processes instead of jumping straight into code.Starting Price: Free -
18
Crewship
Crewship
Crewship is the developer-first platform for deploying AI agent workflows. Deploy your CrewAI, LangGraph, and LangGraph.js agents with a single command and watch them execute in real-time. Key features include one-command deployment, real-time execution streaming, artifact management, auto-scaling, version control, and encrypted secrets management. Crewship handles infrastructure so developers can focus on building great AI agents. Multi-framework support with AutoGen, Pydantic AI, smolagents, OpenAI Agents, Mastra, and Agno coming soon.Starting Price: Free -
19
Overmind
Overmind
Overmind is a model training and deployment platform for teams building AI agents. It ingests production traces through OpenTelemetry and creates datasets from trace data, file uploads, and connectors for Langfuse, LangSmith, Braintrust, and Galileo. Teams can inspect agent context and runtime behavior, prepare and score datasets, evaluate prompts and models against their own examples, and optimize agent behavior through scored changes. The platform supports LoRA and full fine-tuning of open-weight models, benchmarking with configured evaluators, and deployment through an OpenAI-compatible endpoint; trained weights can also be downloaded. Users can work in the hosted console or run the platform on their own infrastructure with Docker Compose. It is designed for AI engineering and product teams operating agents in production that want to test, improve, or specialize models using their own data.Starting Price: Free -
20
eve
Vercel
eve is an open source framework for building AI agents that you own, designed around a file-system-based structure and production-ready runtime. An instructions.md file is enough to define an agent, while optional building blocks such as model configuration, skills, tools, sandboxes, channels, connections, subagents, schedules, and evals can be added as the agent grows. Tools are created by dropping TypeScript files into the tools directory, and skills are written as Markdown playbooks that load only when relevant. Agents can connect to services such as GitHub, Stripe, and Linear through authenticated connections and can surface through Slack, Discord, Teams, web chat, APIs, cron jobs, CLIs, and custom applications from the same codebase. Specialized subagents can handle delegated work with their own prompts, tools, and sandboxes. -
21
Mastra AI
Mastra AI
Mastra is a powerful TypeScript framework for building intelligent AI agents that can execute tasks, access knowledge bases, and maintain memory persistently within workflows. This framework simplifies the process of creating and deploying AI-powered agents by leveraging TypeScript’s capabilities to streamline development. With features like customizable agent instructions, memory, and task orchestration, Mastra provides developers with the tools to build and scale AI agents for various applications, from personal assistants to specialized domain experts.Starting Price: Free -
22
Switch AI
Flint AI
Switch is a collaborative workspace from Flint AI that enables humans and AI agents to work together through existing messaging platforms. The platform creates shared rooms where people, agents, decisions, files, and work history remain available as tasks move between different participants and agents. Teams can bring agents into Slack, Microsoft Teams, Discord, and Mattermost without replacing their existing communication workflows. Switch works with AI and agent technologies including Claude Code, Anthropic Claude, OpenAI, LangChain, LangGraph, Amazon Bedrock, Google Vertex AI, ADK, and custom-built agents. Multiple specialized agents can coordinate within the same room, use work completed by other agents, respond to human direction, and hand tasks to one another while retaining shared context. Switch is extensible by design and is intended to give organizations a common workspace for coordinating human-agent teams without requiring them to migrate to a new collaboration environment.Starting Price: Free -
23
OpenAI Agents SDK
OpenAI
The OpenAI Agents SDK enables you to build agentic AI apps in a lightweight, easy-to-use package with very few abstractions. It's a production-ready upgrade of our previous experimentation for agents, Swarm. The Agents SDK has a very small set of primitives, agents, which are LLMs equipped with instructions and tools; handoffs, which allow agents to delegate to other agents for specific tasks; and guardrails, which enable the inputs to agents to be validated. In combination with Python, these primitives are powerful enough to express complex relationships between tools and agents, and allow you to build real-world applications without a steep learning curve. In addition, the SDK comes with built-in tracing that lets you visualize and debug your agentic flows, evaluate them, and even fine-tune models for your application.Starting Price: Free -
24
OpenAGI
OpenAGI
OpenAGI is a developer-focused framework designed to help teams build autonomous, human-like AI agents capable of planning, reasoning, and executing tasks independently. It bridges the gap between traditional LLM applications and fully autonomous agents by offering tools for decision-making, continual learning, and long-term task execution. The platform allows developers to create specialized agents for real-world use cases across industries such as education, finance, healthcare, and software development. With its flexible architecture, OpenAGI supports sequential, parallel, and dynamic communication patterns between agents. Developers can choose automated configuration generation or manually tailor every detail for complete customization. OpenAGI represents an early but significant step toward making powerful, adaptive agent technology accessible to everyone.Starting Price: Free -
25
AgentForge
AgentForge
AgentForge is a comprehensive SaaS platform that streamlines the creation and customization of AI agents. It offers a fully integrated NextJS boilerplate, enabling users to build, deploy, and test AI applications efficiently. The platform includes pre-built AI agents, customizable graphs, reusable UI components, and an interactive playground for experimentation. AgentForge seamlessly integrates with popular AI tools such as Langchain, Langgraph, Langsmith, OpenAI, Groq, and Llamma, providing all the necessary building blocks for AI application development. With features like observability through Langsmith and over 20 themes via daisyUI, it caters to both small projects and more advanced needs. The platform's straightforward pricing model involves a one-time payment for lifetime access to all features, updates, and improvements, eliminating recurring subscription fees. AgentForge is designed to simplify AI development, making it accessible for developers and businesses.Starting Price: $99 per month -
26
Strands Agents
Strands Agents
Strands Agents is an open-source framework designed to help developers build controllable and flexible AI agents using Python and TypeScript. It enables users to create agents by defining tools as simple functions, eliminating the need for complex workflows or orchestration pipelines. The SDK works with any model and cloud provider, giving developers full freedom in how they deploy and scale their agents. It introduces a streamlined agent loop where the model handles reasoning while developers maintain control through code. Features like steering hooks allow developers to validate and guide agent behavior before and after actions are taken. The platform also includes built-in capabilities such as memory management, observability, and evaluation tools. Overall, Strands Agents SDK simplifies agent development while improving reliability, control, and performance.Starting Price: Free -
27
CopilotKit
CopilotKit
CopilotKit is an enterprise-grade agentic frontend stack designed to help developers build AI-powered applications with generative user interfaces. The platform enables seamless integration between user-facing applications and agentic backends through its AG-UI protocol, which supports bi-directional communication. It provides tools and SDKs for modern frameworks like React, Angular, and Next.js, allowing developers to quickly implement AI features. CopilotKit supports generative UI, enabling AI agents to dynamically render and update interface components in real time. The platform also includes features like chat components, conversation threading, and persistent state management for maintaining context across sessions. Developers can connect their preferred AI models, frameworks, and agents without being locked into a specific ecosystem.Starting Price: $39/developer/month -
28
AG-UI
AG-UI
AG-UI is an open, lightweight, event-based protocol that standardizes how AI agents connect to user-facing applications. Built for simplicity and flexibility, it enables seamless integration between AI agents, real-time user context, and user interfaces. AG-UI is designed for agent-human interaction: during agent executions, backends emit events compatible with standard AG-UI event types, and agent backends can accept simple AG-UI-compatible inputs as arguments. It works with any event transport, including SSE, WebSockets, webhooks, and other streaming systems, while providing a flexible middleware layer that ensures compatibility across diverse environments. AG-UI brings agents into user-facing applications and complements the wider agentic protocol stack: MCP gives agents tools, A2A allows agents to communicate with other agents, and AG-UI connects agents directly to the user interface.Starting Price: Free -
29
LangMem
LangChain
LangMem is a lightweight, flexible Python SDK from LangChain that equips AI agents with long-term memory capabilities, enabling them to extract, store, update, and retrieve meaningful information from past interactions to become smarter and more personalized over time. It supports three memory types and offers both hot-path tools for real-time memory management and background consolidation for efficient updates beyond active sessions. Through a storage-agnostic core API, LangMem integrates seamlessly with any backend and offers native compatibility with LangGraph’s long-term memory store, while also allowing type-safe memory consolidation using schemas defined in Pydantic. Developers can incorporate memory tools into agents using simple primitives to enable seamless memory creation, retrieval, and prompt optimization within conversational flows. -
30
AgentKit
OpenAI
AgentKit is a unified suite of tools designed to streamline the process of building, deploying, and optimizing AI agents. It introduces Agent Builder, a visual canvas that lets developers compose multi-agent workflows via drag-and-drop nodes, set guardrails, preview runs, and version workflows. The Connector Registry centralizes the management of data and tool integrations across workspaces and ensures governance and access control. ChatKit enables frictionless embedding of agentic chat interfaces, customizable to match branding and experience, into web or app environments. To support robust performance and reliability, AgentKit enhances its evaluation infrastructure with datasets, trace grading, automated prompt optimization, and support for third-party models. It also supports reinforcement fine-tuning to push agent capabilities further.Starting Price: Free -
31
Persona
Runtype
Persona is a VanillaJS Agent UI Library that helps developers create agentic front-end experiences for the web in pure JavaScript. Lightweight, extensible, and WebMCP-native, it runs on any stack and can connect to any SSE backend. Developers can start with a floating launcher in the corner, a copilot docked beside an app, or a full-height assistant that owns the page, changing the launcher configuration without changing the agent or app. Persona is designed for support, docs, sales, onboarding, internal tools, and custom agent experiences where the chat UI becomes another way to operate the application. Through WebMCP, developers can expose page actions, search, carts, bookings, forms, and other tools directly in the browser through a document.modelContext; Persona discovers those tools, asks the user before calling them, and streams the result back into the conversation.Starting Price: Free -
32
DemoGPT
Melih Ünsal
DemoGPT is an open source platform that simplifies the creation of LLM (Large Language Model) agents by providing an all-in-one toolkit. It offers tools, frameworks, prompts, and models for rapid agent development. The platform automatically generates LangChain code, which can be used for creating interactive applications with Streamlit. DemoGPT translates user instructions into functional applications through a multi-step process: planning, task creation, and code generation. It supports a streamlined approach to building AI-powered agents, offering an accessible environment for developing sophisticated, production-ready solutions with GPT-3.5-turbo. Additionally, it integrates API usage and external API interaction in future updates.Starting Price: Free -
33
FastAgency
FastAgency
FastAgency is an open source framework designed to accelerate the deployment of multi-agent AI workflows from prototype to production. It provides a unified programming interface compatible with various agentic AI frameworks, enabling developers to deploy agentic workflows in both development and production settings. With features like multi-runtime support, seamless external API integration, and a command-line interface for orchestration, FastAgency simplifies the creation of scalable, production-ready architectures for serving AI workflows. Currently, it supports the AutoGen framework, with plans to extend support to CrewAI, Swarm, and LangGraph in the future. Developers can easily switch between frameworks, choosing the best one for their project's specific needs. FastAgency also features a common programming interface that enables the development of core workflows once and reuse them across various user interfaces without rewriting code.Starting Price: Free -
34
Genspark
Genspark
Genspark is an AI-driven platform that empowers users to automate tasks and generate content with ease, including video production, image creation, and deep research. A standout feature is the Genspark Super Agent, which allows users to delegate tasks like selecting the perfect gifts, planning travel, making restaurant reservations, and even conducting detailed market research. Whether you need to create custom visuals, generate insightful reports, or plan complex trips, Genspark's Super Agent and specialized tools streamline the process, making high-quality outputs accessible without technical expertise.Starting Price: Free -
35
Koog
JetBrains
Koog is a Kotlin‑based framework for building and running AI agents entirely in idiomatic Kotlin, supporting both single‑run agents that process individual inputs and complex workflow agents with custom strategies and configurations. It features pure Kotlin implementation, seamless Model Control Protocol (MCP) integration for enhanced model management, vector embeddings for semantic search, and a flexible system for creating and extending tools that access external systems and APIs. Ready‑to‑use components address common AI engineering challenges, while intelligent history compression optimizes token usage and preserves context. A powerful streaming API enables real‑time response processing and parallel tool calls. Persistent memory allows agents to retain knowledge across sessions and between agents, and comprehensive tracing facilities provide detailed debugging and monitoring.Starting Price: Free -
36
PayOS
PayOS
PayOS is a payment infrastructure platform built specifically for the “agentic” economy, where AI agents and autonomous workflows complete commerce tasks. The system is designed as a card-native solution that enables developers and businesses to embed checkout, billing, and money movement into agentic workflows, supporting all major card networks and offering processor flexibility. It allows a card to be linked once and then used across agent-driven scenarios, while still providing human-in-the-loop controls, strong security (PCI-compliant), and full global network access. PayOS enables both push and pull payments, recurring billing, and autonomous money flows without the need for merchant re-integration. It supports tokenization and collaborations with networks like Mastercard and Visa Intelligent Commerce to open up agentic payment use cases at scale. -
37
AgentScope
AgentScope
AgentScope is an AI-driven agent observability and operations platform that provides visibility, control, and performance analytics for autonomous AI agents across production workloads. It enables engineering and DevOps teams to monitor, diagnose, and optimize complex multi-agent applications in real time by capturing detailed telemetry on agent actions, decisions, resource usage, and outcome quality. With rich dashboards and timelines, AgentScope helps teams trace execution flows, identify bottlenecks, and understand how agents interact with external systems, APIs, and data sources, improving debugging and reliability for autonomous workflows. It supports customizable alerting, log aggregation, and structured event views so teams can quickly surface anomalous behavior or errors across distributed agent fleets. In addition to real-time monitoring, AgentScope provides historical analysis and reporting that help teams measure performance trends, model drift, etc.Starting Price: Free -
38
TF-Agents
Tensorflow
TensorFlow Agents (TF-Agents) is a comprehensive library designed for reinforcement learning in TensorFlow. It simplifies the design, implementation, and testing of new RL algorithms by providing well-tested modular components that can be modified and extended. TF-Agents enables fast code iteration with good test integration and benchmarking. It includes a variety of agents such as DQN, PPO, REINFORCE, SAC, and TD3, each with their respective networks and policies. It also offers tools for building custom environments, policies, and networks, facilitating the creation of complex RL pipelines. TF-Agents supports both Python and TensorFlow environments, allowing for flexibility in development and deployment. It is compatible with TensorFlow 2.x and provides tutorials and guides to help users get started with training agents on standard environments like CartPole. -
39
RA.Aid
RA.Aid
RA.Aid is an open source AI assistant that autonomously handles research, planning, and implementation to expedite software development processes. Built on LangGraph's agent-based task execution framework, RA.Aid operates through a three-stage architecture. RA.Aid supports multiple AI providers, including Anthropic's Claude, OpenAI, OpenRouter, and Gemini, allowing users to select models that best fit their requirements. It also features web research capabilities, enabling the agent to pull real-time information from the internet to enhance its understanding and execution of tasks. It offers an interactive chat mode, allowing users to guide the agent directly, ask questions, or redirect tasks as needed. Additionally, RA.Aid integrates with 'aider' via the '--use-aider' flag to leverage specialized code editing capabilities. It is designed with a human-in-the-loop interaction mode, enabling the agent to seek user input during task execution to ensure higher accuracy.Starting Price: Free -
40
Agent Development Kit (ADK)
Google
The Agent Development Kit (ADK) is a flexible, open-source framework for building and deploying AI agents. It is tightly integrated with Google’s ecosystem, including Gemini models, and supports popular large language models (LLMs). ADK simplifies the development of both simple and complex AI agents, providing a structured environment for building dynamic workflows and multi-agent systems. With built-in tools for orchestration, deployment, and evaluation, ADK helps developers create scalable, modular AI solutions that can be easily deployed on platforms like Gemini Enterprise Agent Platform or Cloud Run.Starting Price: Free -
41
Upsonic
Upsonic
Upsonic is an open source framework that simplifies AI agent development for business needs. It enables developers to build, manage, and deploy agents with integrated Model Context Protocol (MCP) tools across cloud and local environments. Upsonic reduces engineering effort by 60-70% with built-in reliability features and service client architecture. It offers a client-server architecture that isolates agent applications, keeping existing systems healthy and stateless. It provides more reliable agents, scalability, and a task-oriented structure needed for completing real-world cases. Upsonic supports autonomous agent characterization, allowing self-defined goals and backgrounds, and integrates computer-use capabilities for executing human-like tasks. With direct LLM call support, developers can access models without abstraction layers, completing agent tasks faster and more cost-effectively. -
42
OpenChiip Harness
OpenChiip
OpenChiip Harness is a self-hosted AI agent runtime and orchestration framework for developers building local or coordinated agent workflows. It combines LLM conversations, skill orchestration, tool execution, multi-layer memory, resource monitoring, and multi-agent collaboration in a React administration dashboard. Run it as a local service or connect it to the OpenChiip platform for collaborative scheduling. Its CLI, web dashboard, HTTP API, and WebSocket interface support chat, tools, sessions, memory, task management, and monitoring. It supports Baidu ERNIE, OpenAI-compatible model providers, and delegation to Codex or Claude Code. Install via pip or deploy with Docker, Linux packages, systemd, or Windows installers; macOS supports pip installation. Licensed under AIGCGPL-1.0. -
43
Smolagents
Smolagents
Smolagents is an AI agent framework developed to simplify the creation and deployment of intelligent agents with minimal code. It supports code-first agents where agents execute Python code snippets to perform tasks, offering enhanced efficiency compared to traditional JSON-based approaches. Smolagents integrates with large language models like those from Hugging Face, OpenAI, and others, enabling developers to create agents that can control workflows, call functions, and interact with external systems. The framework is designed to be user-friendly, requiring only a few lines of code to define and execute agents. It features secure execution environments, such as sandboxed spaces, for safe code running. Smolagents also promotes collaboration by integrating deeply with the Hugging Face Hub, allowing users to share and import tools. It supports a variety of use cases, from simple tasks to multi-agent workflows, offering flexibility and performance improvements. -
44
Vulnify
Vulnify
Vulnify is runtime authorization for AI agents. Before a sensitive tool call runs, your code calls check() and gets ALLOW, REVIEW or BLOCK, with a 0-100 risk score and the reasons: action, data sensitivity, destination, volume. REVIEW pauses only that action until a person approves. Start in monitor mode, fail closed by default. Policies as code, Node and Python SDKs (MIT) with LangChain, MCP, CrewAI and LangGraph adapters, and a hash-chained audit log with JSON/CSV export. Free plan available.Starting Price: Free plan available -
45
OpenLegion
OpenLegion
OpenLegion is a production-grade AI agent framework and platform for building an AI workforce by describing the team you want. Tell OpenLegion “I want a marketing agency,” “I want a sales team,” or “I want a research desk,” and it deploys the agent stack with roles, budgets, permissions, and secure credential controls built in. Instead of stopping at chat, OpenLegion is designed for real workflows; agents can browse websites, fill out forms, write and run code, send emails and messages, manage files and folders, research and summarize, scrape data, qualify sales leads, process spreadsheets, post to social media, monitor for changes, and trigger workflows through Slack, Telegram, or Discord. Each agent runs in its own isolated container with per-agent budgets, tool permissions, persistent memory, MCP-compatible skills, and vault-secured credentials that agents never touch.Starting Price: $19 per month -
46
CAMEL-AI
CAMEL-AI
CAMEL-AI is the first LLM-based multi-agent framework and an open-source community dedicated to exploring the scaling laws of agents. It enables the creation of customizable agents using modular components tailored for specific tasks, facilitating the development of multi-agent systems that address challenges in autonomous cooperation. The framework serves as a generic infrastructure for various applications, including task automation, data generation, and world simulations. By studying agents on a large scale, CAMEL-AI.org aims to gain valuable insights into their behaviors, capabilities, and potential risks. The community emphasizes rigorous research, balancing urgency with patience, and encourages contributions that enhance infrastructure, improve documentation, and implement research ideas. The platform offers components such as models, tools, memory, and prompts to empower agents, and supports integrations with various external tools and services. -
47
Letta
Letta
Create, deploy, and manage your agents at scale with Letta. Build production applications backed by agent microservices with REST APIs. Letta adds memory to your LLM services to give them advanced reasoning capabilities and transparent long-term memory (powered by MemGPT). We believe that programming agents start with programming memory. Built by the researchers behind MemGPT, introduces self-managed memory for LLMs. Expose the entire sequence of tool calls, reasoning, and decisions that explain agent outputs, right from Letta's Agent Development Environment (ADE). Most systems are built on frameworks that stop at prototyping. Letta' is built by systems engineers for production at scale so the agents you create can increase in utility over time. Interrogate the system, debug your agents, and fine-tune their outputs, all without succumbing to black box services built by Closed AI megacorps.Starting Price: Free -
48
eve
Vercel
Eve is the framework for building agents, like Next.js for web apps, but for agents. It uses Markdown for instructions and skills, TypeScript for tools, and durable execution by default. An agent is a directory that defines instructions and skills in Markdown, tools in TypeScript, and then deploys. Eve compiles the directory, wires up durable workflows, and connects channels, giving developers a structured way to build production agents without gluing together point solutions. An instructions.md file can be a complete agent, while agent.ts lets teams choose a model or configure the runtime. Reusable skills are Markdown playbooks loaded when relevant, so the agent gets focused guidance without carrying everything in every prompt. Tools are added as TypeScript files, with the filename becoming the tool name, and no registration is required. Every agent includes an isolated sandbox and file tools, with support for custom sandbox setup. -
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Claude Managed Agents
Anthropic
Claude Managed Agents is a pre-built, configurable agent system from Anthropic designed to run long-running, asynchronous tasks on managed infrastructure without requiring developers to build their own agent loops. It acts as a complete “agent harness,” allowing developers to define goals while the system handles execution, orchestration, and state management behind the scenes. Unlike direct model prompting, which requires step-by-step interaction, Managed Agents are designed for tasks that unfold over time, such as research, automation, or multi-step workflows, where the agent can continue working independently after being started. It supports advanced capabilities such as multi-agent orchestration, where a primary agent can coordinate specialized sub-agents that operate in parallel with isolated contexts, improving both speed and output quality. -
50
TEN
TEN
TEN (Transformative Extensions Network) is an open source framework designed to empower developers to build real-time multimodal AI agents capable of voice, video, text, image, and data-stream interaction with ultra-low latency. It includes a full ecosystem, TEN Turn Detection, TEN Agent, and TMAN Designer, allowing developers to rapidly assemble human-like, responsive agents that can see, speak, hear, and interact. With support for languages like Python, C++, and Go, it offers flexible deployment on both edge and cloud environments. Using components like graph-based workflow design, drag-and-drop UI (via TMAN Designer), and reusable extensions such as real-time avatars, RAG (Retrieval-Augmented Generation), and image generation, TEN enables highly customizable, scalable agent development with minimal code.Starting Price: Free
