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Lets AI agents save and run reusable protocol chains with persistent memory.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "KAIROS MCP" yet — see the docs or source repo.
Create a reusable protocol chain in KAIROS MCP: when receiving the command 'release a new version,' check the version number, generate a release checklist, verify deployment prerequisites, and store each run result in persistent memory.
A reusable release workflow chain with step definitions, execution order, and stored memory results.
Use KAIROS MCP to design a deterministically executed protocol chain for handling user feedback: first categorize the issue, then match handling rules, and finally produce a standard response while keeping historical records for future reuse.
A stable, reusable feedback-processing chain that follows fixed logic and preserves historical context.
Save a protocol chain in KAIROS MCP for analyzing new feature requests: first extract goals, then identify dependencies and risks, and finally output a conclusion template; run the same steps for each future analysis and record the results.
A standardized requirement analysis chain that supports repeated use, consistent outputs, and persistent records.
Run persistent agent teams and durable workflows with memory, schedules, and goals.
Build AI agent workflows and automate tasks using MCP-connected services.
Let AI agents store, search, and connect typed memories through MCP.
Give AI agents persistent memory, searchable knowledge, and automatic consolidation.
Turn unstructured documents into a searchable knowledge base for AI agents.
Give AI assistants persistent memory, adaptive recall, and graph-based knowledge retrieval.