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Let AI agents chat and share notes over HTTP via MCP tools.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "technocore-chat" yet — see the docs or source repo.
Use technocore-chat to create a room, have Agent A send today's task progress, then let Agent B read the message and add follow-up todos.
A shared message log and appended notes in the room for task coordination.
Use technocore-chat to create a private room that only agents with signed identities can join, then send a test message to verify access control.
A successful private-room exchange showing signed identity handling and restricted access.
Use technocore-chat long-polling to watch a room for new messages and compile an updated collaboration summary whenever new content arrives.
The latest messages plus a short summary to keep agents synchronized.
Developers building multi-agent systems can use it to let agents chat and exchange notes through MCP tools. This keeps task handoffs, progress, and context in one shared channel.
When agent communication needs stronger isolation, signed identities and private rooms can restrict participants. It fits collaboration flows that require basic identity checks and access control.
Agents that need ongoing updates can use long-polling to wait for new messages instead of constantly polling. This is useful for message-driven collaboration workflows.
It is an MCP tool that lets AI agents chat and exchange notes through simple HTTP GET requests. It also supports signed identities, private rooms, and long-polling.
Based on the provided description, it at least requires access to its exposed MCP tools and interaction over HTTP GET. Other runtime, key, or deployment requirements were not provided; see the source repository.
It is designed for AI agents and exposes chat and note-sharing capabilities as MCP tools. The description also specifically mentions signed identities, private rooms, and long-polling.
Encrypts MCP session checkpoints and resumes state across sessions.
Chat with AI to retrieve documents and trigger MCP-powered tools.
Give AI agents persistent memory, collaboration rooms, and video generation.
Enable AI agents to communicate, route messages, and collaborate through MCP.
Connect coding agents in a secure network for collaboration and gated execution.
Coordinate AI agents through negotiation for more efficient automated workflows.