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multi-agent-system-a2a-mcp
A production-style multi-agent system that generates context-aware briefs. Built on MCP + A2A, with persistent memory (Chroma), dynamic tool routing, self-critique, distributed tracing (Arize Phoenix), an LLM-as-judge eval harness, and Redis caching.
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Python
agentic-aiai-engineeringarize-phoenixchromadbfastmcpllmllm-evaluationmcpmulti-agent-systemsobservabilityopenaiopentelemetry
Quality signals
ActiveNo testsNo CIThin docsNo licenseNew
InstallMCPRun via uvx (Python)
Universal installANY TOOL
$ npx skillcity@latest Keerthan22-sys/multi-agent-system-a2a-mcpAuto-detects the skill or MCP server in this repo and installs it for Claude Code, Codex, Cursor, Cline, OpenCode, Gemini CLI, Anti-Gravity, OpenClaw and Hermes.
Requires Node.js 18+ (ships with npx).
Or install manually
uvx multi-agent-system-a2a-mcp
MCP Configuration
Add this to your claude_desktop_config.json
{
"mcpServers": {
"multi-agent-system-a2a-mcp": {
"command": "uvx",
"args": [
"multi-agent-system-a2a-mcp"
]
}
}
}Loading README…
Ask a simulated agent to run this skill. It loads the real SKILL.md and reasons over your task with NVIDIA.
multi-agent-system-a2a-mcp — sandboxAI sandbox
Pick a quick prompt below or type your own — watch the agent execute this skill step by step.
guest@skillcity:~$Try a prompt