v2.1.1 · MIT
Analytics tool for MCP (Model Context Protocol) servers and AI agents - tracks tool usage patterns and provides insights
— · MIT
Open-source coding agents memory. Records issues, attempts, fixes and decisions, then warns your agent before it repeats an approach that already failed. Native MCP server for Claude Code, Cursor, Antigravity and Codex. 100% local, no cloud, no telemetry. MIT.
— · Apache-2.0
Shared Single-file memory layer for all your agents, sub mili-second RAG over text, photo and video on Apple Silicon.. No Server. No API. One File. Pure Swift
v0.10.2 · no license
Open-source adversary emulation for AI agents and MCP servers.
— · Apache-2.0
Local code intelligence MCP server and CLI for AI coding agents
— · MIT
Git-native persistent memory for AI coding agents. Implements Google OKF v0.2 with sub-300µs in-memory BM25 search, embedded MCP server, and progressive disclosure. Slashes token bloat by 80% with zero external databases or dependencies. Built in pure Go.
v1.0.21 · no license
Browser automation and computer use for AI agents. One CLI and MCP server for your signed-in browser, native macOS apps, and real iPhones.
v0.27.3 · MIT
Linter for AI agent context files and MCP configs: CLAUDE.md, AGENTS.md, .cursorrules, .mcp.json - catches broken paths, wrong commands, leaked secrets
v3.1.9 · no license
一个自主的高级智能伙伴,不仅分析问题,更持续工作直到完成实现和验证。
— · no license
✨ All your agents and workspaces in one place, on every device you own. Track tasks on a board, accessible from desktop, mobile, browser, or API. Self-hosted.
v7.69.5 · AGPL-3.0-or-later
My Claude Code (MCC): a local multi-provider LLM proxy, model router and control plane for Claude Code, Codex, OpenCode, Gemini CLI and other AI coding agents, with 57 providers, fallback routing, credential health, a native web-search tool proxy, and ana
v1.0.33 · MIT
GodPrompt MCP server + portable Agent Skill for coding agents — TDD, debugging, verification gates, task routing, and progressive disclosure.
v1.5.5 · MIT
sofagent is an open-source FDE Harness for AI coding agents — on entry, write your business judgment into files (workflows, ontology, AI nodes); after departure, audit every change against them. 25 codified audit rules, tamper-evident chain, snapshots, and an MCP toolset (104 tools, 11 plugins). Everything can be FDEing.
— · MIT
🏛️ The patent plugin for AI coding agents — turn technical ideas into patent disclosures with Claude Code, Codex, and OpenCode.
v0.6.3 · Apache-2.0
Synchronize and Orchestrate agents from CLI to GUI, across desktop to phone.
— · MIT
Stop agents from over-engineering. Inspired by Ponytail, but without the plugin madness. Just one AGENTS.md file.
v1.4.2 · MIT
Multi-registry skill discovery and installation for AI coding agents — search 9 sources, score, paginate, and install agent skills with security labels
— · no license
Build agentic systems. Run them with confidence. Orchestrate agents, automate business processes, inspect every execution, and keep humans in control. Deploy Heym on your own infrastructure.
— · no license
Structural memory for AI coding agents. Bi-temporal graph, MCP-native, zero LLM calls. Cursor · Claude Code · Codex · DeepSeek Harness · Hermes · VS Code · Windsurf.
— · MIT
Runtime evidence that helps agents trace, profile, and burn down hotspots in application and native code, GPU kernels, and inference stacks.
v1.6.2 · MIT
Persistent project knowledge graph for coding agents. MCP server with semantic search, in-process embeddings, and web explorer.
— · MIT
Kindly Web Search MCP Server: Web search + robust content retrieval for AI coding tools (Claude Code, Codex, Cursor, GitHub Copilot, Gemini, etc.) and AI agents (Claude Desktop, OpenClaw, Hermes, etc.). Supports Serper, Tavily, and SearXNG.
— · Apache-2.0
Config-driven engine that turns JSON into production-grade AI agents. Multi-agent orchestration, 12+ LLM providers, MCP/A2A protocols, RAG, persistent memory, and enterprise compliance (EU AI Act, GDPR, HIPAA). Built on Quarkus.
v0.3.56 · MIT
Version-controlled project context for AI coding agents: code graph, architecture wiki, project memory, relevant tests, quality signals, and task flows.