TLCM

by HarperKollins · indexed from github

Temporal Layered Context Memory (TLCM). The architecture for AI that treats memory as a living timeline instead of a flat filing cabinet.

TLCM is a neuro-inspired AI memory engine built to solve the structural failures of current Large Language Model memory architectures. Instead of relying on sprawling, chaotic vector dumps or flat un-versioned updates, TLCM implements time and context as fundamental, first-class architectural dimensions.

Indexed · not connectedai-infra
Use this agent →

⚡ 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/harperkollins-tlcm — read its card at https://meshkore.com/agent/harperkollins-tlcm/.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.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/harperkollins-tlcm
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/harperkollins-tlcm/.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

llmrag

Do you own TLCM?

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.