The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Clarilayer
Memory for your AI work across projects and sessions. Save decisions, rules and lessons with source and applicability. Connect over MCP.
Install
npx clarilayer@latest instructions --agent codexclaude mcp add clarilayer -- npx clarilayer@latest instructions --agent codex{
"mcpServers": {
"clarilayer": {
"command": "npx",
"args": [
"clarilayer@latest",
"instructions",
"--agent",
"codex"
]
}
}
}Install command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →ClariLayer
Your AI should remember how you work. Turn selected past conversations into memory your AI can use across projects and sessions.
Website · Docs · Connect your AI · Quickstart
ClariLayer keeps the facts, preferences, decisions, rules and lessons you choose to carry forward. Connect Claude Code, Cursor, Codex, claude.ai or another compatible remote MCP client. Your AI can recall relevant work context from the selected authorized space, with its source and applicability visible.
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One decision, carried into the next session
You settle a launch decision with your AI:
For the Launch project, show the product demo first. Technical detail belongs in docs. Remember this confirmed decision with its source and project applicability.
In a later session:
Recall the Launch project's saved decisions before drafting the launch page. Show which decision applies and where it came from.
The decision can travel across projects and sessions within the authorized space while retaining its original applicability. A rule for one customer or project stays bounded. If it changes, correct it; if it no longer belongs, use scoped forget or exclusion.
Recall depends on the AI client actually calling the tool. Connecting MCP does not guarantee every answer uses saved context.
Connect your AI
Use Connect your AI for guided setup. Select your client and space, give the setup request to that AI, and complete authentication in the client. Use OAuth when the selected route supports it, or store a context key locally as the fallback. Never paste a key into an AI conversation or a GitHub issue.
Already connected? Choose Update my AI setup on the same page, then run its request in the intended project. This updates one recognized ClariLayer instruction block while preserving your own instructions.
| Client | Project instruction target |
|---|---|
| Claude Code | CLAUDE.md |
| Codex | AGENTS.md |
| Cursor | .cursor/rules/clarilayer.mdc |
| claude.ai / other remote clients | Follow the connection and runtime guidance supported by that client |
The installed bootstrap obtains the current workflow from get_project_stanza with mode: "runtime" once at the first relevant use in each new AI session. A routine server guidance update then reaches the next session without copying another long workflow into every project.
Optional setup CLI
The npm CLI supports context-key connection setup and a local dbt check. CLI 0.3.0 replaces the embedded Analytics instructions with a request for your connected AI and adds instructions --agent <client>.
Check which version is available before choosing a command:
npm view clarilayer version
With 0.3.0 or later available:
npx clarilayer@latest init
# Already connected? Print only the instruction update request:
npx clarilayer@latest instructions --agent codex
If your registry still serves 0.2.1, use npx clarilayer@0.2.1 init --no-stanza to skip its older embedded instructions, then complete Update my AI setup through the guided setup above. The hosted path is available independently of npm publication.
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