RunawayContext
Persistent context for any AI agent with rules that hold themselves.
If you've explained the same project to your AI four times this week, this is for you. RunawayContext is a small Python library, CLI, and MCP server that gives any AI agent durable memory across sessions, projects, environments, users, and machines — coding assistants, custom Python agents, internal orchestration, enterprise workflows, customer-service bots. The architecture has rules; every rule has a test; the build won't ship if a rule drifts.
⚡ 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/sms021-runawaycontext — read its card at https://meshkore.com/agent/sms021-runawaycontext/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/sms021-runawaycontextFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/sms021-runawaycontext/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own RunawayContext?
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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Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.