awesome-repositories.com
© 2026 Bringes Technology SRL·VAT RO45896025·hello@bringes.io
MCPSitemapPrivacyTerms
Agent Frameworks · Awesome GitHub Repositories

15 repos

Awesome GitHub RepositoriesAgent Frameworks

Software structures providing abstractions, runtimes, and configuration standards for building, managing, and executing language model-powered applications.

Explore 15 awesome GitHub repositories matching artificial intelligence & ml · Agent Frameworks. Refine with filters or upvote what's useful.

  1. Home
  2. Artificial Intelligence & ML
  3. Artificial Intelligence & Machine Learning
  4. Agent Development Frameworks
  5. Architectural Frameworks and Ecosystems
  6. Agent Frameworks

Awesome Agent Frameworks GitHub Repositories

Describe the repository you're looking for…
We'll search the best matching repositories with AI.
  • openclaw/openclaw

    openclaw/openclaw

    211,971GitHubView on GitHub↗

    Openclaw is a platform for managing agent execution environments, providing the infrastructure to control agent lifecycles, session state, and workspace persistence. It features a centralized gateway that handles model loops, tool invocation, and streaming events, while supporting multi-agent routing and persistent mem

    TypeScriptaiassistantcrustacean
  • Significant-Gravitas/AutoGPT

    Significant-Gravitas/AutoGPT

    181,891GitHubView on GitHub↗

    AutoGPT is an orchestration platform designed for building, managing, and deploying autonomous agents. It provides a visual canvas-based environment where users can assemble agents by connecting modular blocks that represent actions, data flows, and conditional logic. The platform supports the entire agent lifecycle, i

    Pythonaiartificial-intelligenceautonomous-agents
  • langchain-ai/langchain

    langchain-ai/langchain

    127,015GitHubView on GitHub↗

    LangChain is an orchestration framework designed for building, managing, and deploying applications powered by large language models. It provides a unified integration layer that normalizes disparate model provider APIs into a consistent set of primitives, enabling developers to build complex, multi-step AI workflows t

    Pythonagentsaiai-agents
  • google-gemini/gemini-cli

    google-gemini/gemini-cli

    94,954GitHubView on GitHub↗

    This project provides a command-line interface for managing autonomous agent workflows, task orchestration, and system-level automation. It includes a comprehensive framework for defining agent skills, managing persistent memory, and delegating tasks to specialized subagents. Users can configure complex planning modes,

    TypeScriptaiai-agentscli
  • florinpop17/app-ideas

    florinpop17/app-ideas

    90,567GitHubView on GitHub↗

    App-ideas is a development platform that integrates autonomous AI agents into local environments to orchestrate code review, automated fix application, and workflow management. It functions as a command-line interface that connects external AI assistants to your codebase, enabling iterative development cycles through p

    applicationscodingcodingchallenges
  • browser-use/browser-use

    browser-use/browser-use

    78,576GitHubView on GitHub↗

    Browser-use is a framework for building autonomous agents that navigate, interact with, and extract data from web interfaces using natural language instructions. By acting as an orchestration layer between large language models and browser automation protocols, it enables the execution of complex, multi-step workflows

    Pythonai-agentsai-toolsbrowser-automation
  • infiniflow/ragflow

    infiniflow/ragflow

    73,425GitHubView on GitHub↗

    This project is a comprehensive retrieval-augmented generation platform designed for building, managing, and deploying knowledge-based AI applications. It provides a unified environment for organizing datasets, configuring conversational chat assistants, and developing autonomous agents that execute multi-step reasonin

    Pythonagentagenticagentic-ai
  • anthropics/skills

    anthropics/skills

    71,987GitHubView on GitHub↗

    This project provides a standardized framework for extending the functional range of artificial intelligence agents through a registry of modular, declarative instructions. It enables agentic workflow automation by allowing developers to define task-specific behaviors and operational constraints that guide how agents i

    Pythonagent-skills
  • dair-ai/Prompt-Engineering-Guide

    dair-ai/Prompt-Engineering-Guide

    70,526GitHubView on GitHub↗

    This project is a comprehensive educational resource and knowledge base dedicated to the development and application of large language models and autonomous agentic systems. It provides a structured framework for understanding prompt engineering, context management, and the architectural patterns required to build task

    MDXagentagentsai-agents
  • OpenHands/OpenHands

    OpenHands/OpenHands

    67,974GitHubView on GitHub↗

    OpenHands is an autonomous agent framework designed for software engineering workflows. It provides a modular platform for orchestrating AI agents that reason, plan, and execute tasks within isolated, containerized development environments. By integrating with standard version control and development tools, the system

    Pythonagentartificial-intelligencechatgpt
  • FoundationAgents/MetaGPT

    FoundationAgents/MetaGPT

    64,304GitHubView on GitHub↗

    MetaGPT is an agentic workflow engine and multi-agent orchestration framework designed to automate complex software engineering and data analysis tasks. It functions as an automated software factory that transforms high-level natural language requirements into functional web applications, technical documentation, and p

    Pythonagentgptllm
  • cline/cline

    cline/cline

    58,164GitHubView on GitHub↗

    Cline is an extensible agent runtime and multi-agent orchestration engine designed to automate complex software engineering workflows. It functions as an integrated development environment extension that bridges strategic task planning with autonomous execution, allowing users to manage multi-step projects through huma

    TypeScript
  • AntonOsika/gpt-engineer

    AntonOsika/gpt-engineer

    55,201GitHubView on GitHub↗

    GPT-Engineer is an autonomous agent and framework designed for AI-assisted software development. It functions as a generative codebase architect that translates natural language requirements into complete, functional software projects by reading and writing files directly to the local file system. The platform disting

    Pythonaiautonomous-agentcode-generation
  • microsoft/autogen

    microsoft/autogen

    54,656GitHubView on GitHub↗

    This framework provides a development environment for building collaborative systems where autonomous agents interact to solve complex tasks through conversational workflows. It functions as a conversational workflow engine and event-driven runtime, coordinating multi-step processes by translating high-level goals into

    Pythonagenticagentic-agiagents
  • FoundationAgents/OpenManus

    FoundationAgents/OpenManus

    54,544GitHubView on GitHub↗

    OpenManus is an autonomous agent framework designed to build intelligent software entities capable of executing complex, multi-step tasks through independent decision-making. It functions as a workflow orchestration engine that uses a central language model to interpret user goals, break them down into actionable steps

    Python

Explore sub-tags

  • Agent Action RepresentationsStandardized formats for encoding agent decisions, tool usage, and reasoning steps.
  • Agent Configuration FormatsDeclarative file-based schemas for defining agent identity, system prompts, and tool availability.
  • Agent Configuration ProfilesSettings and environment definitions for initializing agent instances.
Agent Configuration Schemas
Standardized formats for defining agent behavior, persona, identity, memory, and tool availability.
  • Agent Configuration SpecificationsStandardized formats for defining agent behaviors, tool access, and operational constraints.
  • Agent Configuration StandardsMechanisms for defining project-wide guidelines and coding standards for agent execution.
  • Agent Design PatternsConceptual frameworks and architectural strategies for constructing effective LLM-based agents.
  • Agent Evaluation FrameworksSystems for assessing agent decision-making, action success, and conversation quality through automated scoring and feedback loops.
  • Agent Execution Runtimes1 sub-tagCore engines that manage the serialized execution loop, state persistence, and tool orchestration for AI agents.
  • Agent Management APIsAPI endpoints for the lifecycle management of autonomous agents.
  • Agent OrchestratorsSystems that manage the lifecycle, reasoning loops, and multi-agent delegation strategies for language model-based agents.
  • Agent Performance MetricsQuantitative measures for evaluating the effectiveness and reliability of AI agent workflows.
  • Agent Persona DefinitionsConfigurations that define the specific system prompts, behavioral constraints, and specialized capabilities for individual agents within a system.
  • Agent Prompt TemplatesSystems for defining and managing reusable system prompt structures to control agent behavior and reasoning.
  • Agent Querying InterfacesMechanisms for inspecting agent state, task progress, or conversation history without altering the agent's execution flow.
  • Agent Refinement WorkflowsMechanisms for agents to iteratively review and improve their own output based on quality metrics.
  • Agent RegistriesMechanisms for registering and managing collections of specialized sub-agents for task delegation.
  • Agent Runtimes6 sub-tagsBackend environments that manage the execution loop, tool invocation, prompt processing, and lifecycle of autonomous agents.
  • Agent Skill DefinitionsStandardized structures for defining reusable capabilities, instructions, and task triggers for autonomous agents.
  • Agent Task RefinementMechanisms for automatically iterating on agent prompts or outputs based on performance feedback loops until success criteria are achieved.
  • Agent Tool ExecutionMechanisms for agents to invoke external functions or tools, including security and confirmation workflows.
  • Agent Tool IntegrationsMechanisms for connecting autonomous agents to external software tools, APIs, or services to extend their functional capabilities.
  • Agent Tooling DefinitionsFrameworks for registering and packaging custom functions or tools for use by autonomous agents in remote environments.
  • Agent Tooling InterfacesFrameworks for defining and registering custom tools that agents can invoke to perform specific actions.
  • Agent Tooling RegistriesSystems for defining, registering, and managing the specific capabilities and tools available to autonomous agents.
  • Agentic Tool-Use FrameworksFrameworks enabling agents to interact with external tools and knowledge bases.
  • Autonomous Agent DefinitionsConfiguration and logic for defining agent behaviors and capabilities.
  • Context Validation FrameworksMethods and tools for evaluating the completeness and accuracy of context provided to AI agents.
  • Custom Tool DefinitionsFrameworks for defining custom tools by extending base classes with specific action and observation schemas.
  • Event-Driven Agent RuntimesExecution environments that manage asynchronous message passing and state transitions for distributed agent architectures.
  • Execution HooksMechanisms for triggering custom logic during agent command lifecycles.
  • External Service IntegrationsMechanisms for connecting autonomous agents to third-party APIs, data sources, and external software tools.
  • LLM-Driven Agent LoopsSystems that orchestrate iterative task execution by processing environmental context and generating actionable commands via language models.
  • Message ProtocolsStandardized interfaces for injecting system or user messages into agent prompt contexts.
  • Multi-Agent Orchestration FrameworksDevelopment environments that coordinate multiple specialized autonomous agents to execute complex collaborative tasks.
  • Multi-Agent Orchestration PatternsArchitectural strategies for coordinating multiple specialized agents to decompose and execute complex workflows.
  • Parallel Tool ExecutionConcurrent execution of multiple tools by an agent.
  • Plugin Management SystemsConfiguration-driven systems that manage the installation, lifecycle, and activation of plugins for agent frameworks.
  • Plugin-Based Agent IntegrationsStandardized interfaces for external AI assistants.
  • Role-Based Agent OrchestrationFrameworks that coordinate multiple agents by assigning specific roles and operating procedures to complete complex tasks.
  • Runtime Compatibility ContractsSpecifications defining the interface and lifecycle responsibilities between an agent runtime and its execution environment.
  • Task Delegation ConfigurationsSettings and schemas for defining sub-agent roles, specialized skill sets, and autonomous task distribution workflows.
  • Tool Definition AdaptersNormalization layers that standardize disparate tool-execution signatures for consistent agent-based tool invocation.
  • Tool Definition PatternsGuidelines and best practices for defining functions and tools for LLM agent execution.
  • Tool Registration SystemsMechanisms for defining and exposing functional tools to agentic reasoning engines.
  • Tool-Binding InterfacesAbstraction layers that map natural language instructions to executable functions and external API calls.
  • Workflow OrchestratorsTools that manage sequences of prompts and tool calls to achieve high-level programming objectives.