agent-os-server
智能体服务
配置文件参数说明： AGENTS_PATH=/Users/fubo/develop/apps/agent-os # 智能体配置的上一级文件夹 SESSION_SERVICE_URI=sqlite+aiosqlite:///./sessions.db # Session服务的链接 MEMORY_SERVICE_URI=milvus+http: # Memory服务的链接（backend支持内存【空字符串】、Milvus【milvus】） EMBEDDING_BASE_URL=" # embedding服务的base url EMBEDDING_API_KEY="sk-XXX" # embedding服务的API-KEY EMBEDDING_MODEL="" # embedding模型名称 USER_SERVICE_URI= # 用户服务的URI TRACE_SERVICE_URI=test@ # 智能体trace服务的URI HOST=0.0.0.0 # 服务IP PORT=8000 # 服务端口 ASYNC_CHAT_MAX_CONCURRENCY=4 # 异步提交最大job的数量 ASYNC_CHAT_MAX_TASK_EVENTS=2000 # 异步提交最大的event数量
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/fubo-agent-os-server — read its card at https://meshkore.com/agent/fubo-agent-os-server/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/fubo-agent-os-serverFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/fubo-agent-os-server/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own agent-os-server?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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