SignalMesh: The Open Source Ambient Context Layer for AI Agent Fleets

99.97% cost reduction on context reads. 1.69µs retrieval. Drop-in with LangChain, CrewAI, AutoGen. Your agents are making tool calls to read context that hasn't changed. Each one costs: 800ms+ round-trip latency Scaffold tokens burned on the same boilerplate API cost, repeated per agent, per request With 5 agents and 3 context reads each: $1,387/year on reads alone. pip install signalmesh # or self-host via Docker from signalmesh import signal_registry # Any source broadcasts signal_registry.broadcast("market_data", "rss", {"btc": 42000}) # Any agent tunes in — 1.69µs, no network, no tokens context = signal_registry.tune_in(["market_data", "price"]) The mesh is in-memory, per-frequency buffered (last 100 signals), and keyword-flexible — agents find context even when their keyword doesn't exactly match the frequency name. The public mesh is running at https://acecalisto3-signalmesh.hf.space: 27 active frequencies Real external agent traffic CORS open, no auth required 7 REST endpoints curl https://acecalisto3-signalmesh.hf.space/ui/frequencies # all live frequencies curl https://acecalisto3-signalmesh.hf.space/ui/status # mesh health + signal count Metric Value tune_in() latency (single agent) 1.69 µs tune_in() latency (100 concurrent) ~1.25 ms Cost vs tool call architecture -99.97% Payload size impact on latency negligible (refs, not copies) No schema changes. No migration. Broadcast from wherever you produce context: # LangChain tool → mesh @tool def fetch_and_broadcast(query: str): data = your_api.get(query) signal_registry.broadcast(query, "tool", data) return data # CrewAI agent reads from mesh instead of calling tool context = signal_registry.tune_in(["query_keyword"]) Open Source Managed Cloud Enterprise Price Free (MIT) $299/mo Custom Nodes Unlimited (self-host) 500 Unlimited SLA — 99.9% 99.99% Support Community Email + Slack Dedicated engineer Custom implementations (LangGraph, AutoGen, CrewAI integration) available — flat-rate, delivery in days. Interactive demo: https://kyklos.io HuggingFace Space: https://acecalisto3-signalmesh.hf.space GitHub (MIT): https://github.com/Ig0tU/SignalMesh Enterprise: abra.autopreneur@gmail.com