by AlgoNoRhythm · MCP Server · ★ 291
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
The graph based agentic IDE
| Stars | 291 |
| Forks | 33 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 44.9261138597499/100 |
| Open Issues | 2 |
| Last Updated | 2026-09-13 |
| Created | 2026-08-02 |
| Platforms | mcp, node |
| Est. Tokens | ~13k |
These tools work well together with Flare for enhanced workflows:
Looking for a Flare alternative? If you're comparing Flare with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Open-source Agentic AI framework in Go for building, orchestrating, and deploying intelligent agents. LLM-agno
AI coding dream team of agents for VS Code. Claude Code + openai Codex collaborate in brainstorm mode, debate
Model-agnostic plug-n-play LangChain/LangGraph agents powered entirely by MCP tools over HTTP/SSE.
🚀 Universal SDK for building next-gen MCP servers
🌋 Build AI agents that seamlessly combine LLM reasoning with real-world actions via MCP tools — in just a few
Daymon puts your favorite AI to work 24/7. It schedules, remembers, and orchestrates your own virtual team. Fr
Explore other popular mcp server tools:
Flare is The graph based agentic IDE. It is categorized as a MCP Server with 291 GitHub stars.
Flare is primarily written in TypeScript. It covers topics such as agent, agent-orchestration, agentic-ai.
You can find installation instructions and usage details in the Flare GitHub repository at github.com/AlgoNoRhythm/Flare. The project has 291 stars and 33 forks, indicating an active community.
Flare is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Flare on Agent Skills Hub include AgenticGoKit, Mysti, DeepMCPAgent. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: