Open Source AI Agents
AI agents are software systems that use language models and other tools to pursue goals through multiple steps. They can interpret requests, plan actions, call APIs, search or modify data, and adjust their approach based on results. Agent systems help automate work that involves decisions and changing context, while enabling people to delegate repeatable tasks or coordinate specialized capabilities.
Open source tools in this area include agent frameworks, orchestration libraries, workflow templates, skills, interfaces, and memory or tool-integration components. When choosing one, consider its maturity, license, maintenance activity, model and infrastructure requirements, security controls, and compatibility with your existing systems. These tools are useful to developers building agent-powered applications, teams automating workflows, and researchers exploring how agents behave and collaborate.
425 repositories · updated October 17, 2026
Cymatix-Context: Deterministic RAG for Agents with SQLite
Cymatix Context is a local-first retrieval system for agents, built on SQLite FTS5 BM25. It returns a know-or-miss result without an LLM call on the retrieval path, through CLI, HTTP, and MCP interfaces.
ActiveHealth 60/100
LibrAgent: A Tauri Desktop Environment for AI Agents
LibrAgent is a Tauri desktop environment for running AI agents with local workspaces, MCP tools, and built-in coordination patterns. Choose a cloud or Ollama model, then use the same workflow on Windows, macOS, or Linux.
ActiveHealth 72/100
open-timeline-engine: Shared Memory for AI Agents via MCP
Open Timeline Engine is a local-first Python context engine for MCP-compatible agents such as Claude, Codex, and Cursor. It captures work over time, finds recurring patterns, and returns past decisions with citations and safety gates.
ActiveHealth 32/100
agent-skills: Share Agent Skills Across Coding Assistants
A maintained catalog of reusable skills for GitHub Copilot, Claude Code, and Codex. It provides cross-client guidance, host-aware routing, and scripts for validating and syncing skills to approved personal folders.
ActiveHealth 21/100
awesome-agent-skills: Track AI Agent Skill Repositories
A GitHub Actions-powered directory that refreshes a list of AI agent skill repositories every 15 minutes. Useful for discovering current projects across agent ecosystems, though its README does not explain how skills are vetted or rated.
NewHealth 36/100
agentrc: Prepare Repositories for AI Coding Agents
AgentRC assesses a repository’s readiness for AI coding agents, then generates tailored instructions and development configuration. It can also evaluate those instructions over time, making it useful for teams that want agent context grounded in their codebase.
ActiveHealth 69/100
RLM: Process Large Documents in LLM-Sized Chunks
RLM is a .NET CLI for breaking large documents into manageable chunks, processing them across multiple turns, and combining the results. It suits developers using Claude Code or scripts to work with content that exceeds an LLM's context window.
QuietHealth 25/100
model-harness: Build Controllable AI Agents for .NET
A ports-and-adapters framework for building bounded, extensible AI agents in .NET. It combines a model loop with context-shaping guides, safety sensors, tools and budget controls, with adapters for Anthropic, Azure OpenAI and Ollama.
NewHealth 54/100
ContextTax: Measure MCP Tool Costs in an AI Context Window
ContextTax is a cross-platform CLI that measures how much MCP tool schemas and responses consume from an AI agent’s context window. Use Anthropic token counting for ground-truth figures or an offline estimate when you do not have an API key.
QuietHealth 20/100
SocratiCode: Give AI Agents Searchable Codebase Context
SocratiCode is a local-first MCP server and plugin that helps AI agents explore large codebases with semantic search, dependency graphs, and symbol-level impact analysis. It also indexes project context such as API specs and database schemas.
ActiveHealth 75/100
ace: Evolve LLM Contexts Through Agent Experience
ACE helps language-agent teams build and refine reusable playbooks from task outcomes, rather than repeatedly rewriting prompts or fine-tuning models. It suits teams experimenting with offline or online adaptation for agent tasks and domain-specific reasoning.
MaintainedHealth 37/100
agent-feed: Govern AI Coding Workflows in Your Repository
Agent Feed installs a repository-owned workflow for AI coding tools, with shared instructions, task and review gates, checks, and tool adapters. It suits teams that want consistent, verifiable AI-assisted changes across Codex, Claude Code, and Cursor.
QuietHealth 22/100