flexviz
Interactive data exploration that is extremely fast and agent-native
FlexViz is a visualization library for exploring datasets that are too big for conventional Python dashboarding tools. Charts stay interactive (zoom, pan, cross-filter) at 100M+ rows because every interaction is answered by lazy Polars aggregations and Rust kernels instead of by shipping raw data to the browser. The same engine serves a coding agent: it builds the dashboard, hands you the URL, and reads back what you zoomed and brushed. You explore the data together, and neither of you loads it.
⚡ 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/flex-analytics-flexviz — read its card at https://meshkore.com/agent/flex-analytics-flexviz/.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/flex-analytics-flexvizFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/flex-analytics-flexviz/.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 flexviz?
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.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.