Open Source AI Agents
Discover 404 open source AI Agents repositories from GitHub, each with an analysis of what it does, key features, use cases and alternatives. AI Agents projects here are most often combined with Python, Developer Tools and MCP. Last updated October 4, 2026.
404 repositories · updated October 4, 2026
dify-official-plugins: Extend Dify with Models and Tools
Official plugins for Dify add models, tools, agent strategies, and HTTP webhook extensions to the platform. Use this repository when building or managing Dify applications that need these integrations.
awesome-ai-agents: Discover AI Agent Tools and Research
A community-curated directory of AI agent frameworks, platforms, infrastructure, evaluation tools, safety resources, papers, and learning materials. Use it to survey the ecosystem and find options for a particular agent-building need.
agentskills: Standardize Skills for AI Agents
Agent Skills defines an open format for packaging instructions, resources, and optional scripts that give AI agents specialized capabilities. Use it to create portable, reusable workflows for compatible agent tools.
skills: Give AI Agents Google Product Guidance
Google Skills is a collection of task-focused instructions for AI agents working with Google products and technologies, especially Google Cloud. Install selected skills through the Skills CLI or use the bundled plugins with supported agent harnesses.
agent-skills: Give AI Coding Tools HashiCorp Product Guidance
HashiCorp Agent Skills provides reusable guidance for AI coding tools working with Terraform and Packer. Install individual skills or product plugin bundles, and check the catalog for supported paths and lifecycle status.
a-mem-mcp: Build Evolving Memory for Coding Agents
A-MEM is an MCP server and Python library that stores agent knowledge as an evolving, connected memory graph. It suits coding-agent users who need to retrieve and build on project context across sessions.
agent-skills: Structure AI-Assisted Development from Specs to PRs
A collection of reusable skills for AI coding agents, covering specification writing, implementation, review, testing, and autonomous sprint workflows. Useful for teams that want repeatable processes and clearer quality gates across agent sessions.
agent-sandbox: Run Coding Agents in a Locked-Down Environment
Agent Sandbox runs AI coding agents in Docker containers with restricted workspace access and default-deny network controls. It suits developers who want to limit an agent’s access to local files, network services, and credentials while retaining CLI or IDE workflows.
Agent-Memory: Persistent Memory for AI Coding Agents
Agent-Memory gives coding agents persistent, searchable memory across sessions and tools. It is aimed at developers using MCP-compatible agents who want automatic context capture and recall without repeatedly explaining their projects.
anythingmcp: Turn APIs and Databases into MCP Tools
AnythingMCP is a self-hosted gateway that turns REST, SOAP, GraphQL, OData, and SQL systems into tools for MCP-compatible AI clients. It combines connector generation with access controls and auditing for teams that want AI access to existing systems.
gh-aw-firewall: Restrict Network Access for Agentic Workflows
A Docker-based firewall for running agentic workflow commands with outbound traffic limited to approved domains. It also isolates LLM credentials in a sidecar, making it useful for teams that need tighter network and secret controls around automated agents.
skills: Give AI Agents AMD Workflow Guidance
AMD Skills is a catalog of task-focused instructions and tools that help coding agents work with AMD hardware and software. Install selected skills into compatible agents when you need guidance for workflows such as local AI, ROCm troubleshooting, or LLM serving.