AgentMemory Adapter

Install, wire, audit, and harden AgentMemory for AI coding agents and project workspaces. Use when Codex needs to adopt rohitg00/agentmemory, configure Codex or OpenClaw memory integration, create ClawHub-ready AgentMemory guidance, debug MCP/hook/plugin setup, verify memory capture, or handle edge cases such as npx stalls, sandbox localhost routing, duplicate plugin paths, stale Codex hooks, remote bearer-token security, multi-agent isolation, or missing full-tool proxy mode.

Use this skill to make AgentMemory a dependable shared memory layer, not just a copied MCP snippet.

First Pass

1. Inspect the target agent and project scope before editing config. Prefer user-level integration for "all current projects"; prefer repo-local integration only when the user asks for project-specific behavior.
2. Read references/agentmemory-deep-analysis.md for the current AgentMemory architecture and references/platform-recipes.md for exact Codex, OpenClaw, and ClawHub-ready patterns.
3. Run scripts/check_agentmemory.py before and after changes. Use --url <base-url> when the server is remote or uses a non-default port.
4. Preserve existing user config and backups. agentmemory connect writes backups under ~/.agentmemory/backups; manual JSON/TOML edits should be equally scoped.

Install Strategy

Prefer a stable local command over unbounded npx in long-lived MCP configs:

npm install --prefix ~/.agentmemory/npm @agentmemory/agentmemory@0.9.22 --omit=optional
ln -sfn ~/.agentmemory/npm/node_modules/.bin/agentmemory ~/.local/bin/agentmemory

Use full optional dependencies only when the user explicitly needs local vector/image embeddings and accepts native package install cost. If npx @agentmemory/agentmemory@latest stalls, install the core package locally as above and point MCP entries at ~/.local/bin/agentmemory mcp.

Codex Workflow

1. Wire MCP with the local command:

codex mcp remove agentmemory 2>/dev/null || true
codex mcp add agentmemory \
  --env AGENTMEMORY_URL=http://localhost:3111 \
  --env AGENTMEMORY_TOOLS=all \
  -- ~/.local/bin/agentmemory mcp

2. Install the Codex hook fallback when Codex Desktop or plugin-local hooks are unreliable:

agentmemory connect codex --with-hooks --force

Then re-run the MCP add command above if connect rewrites the server back to npx.

3. Install the upstream Codex plugin or a local marketplace copy when slash skills are wanted. Patch the plugin .mcp.json to the local command if avoiding npx.

4. Verify:

codex mcp list
python3 ~/.codex/skills/agentmemory-adapter/scripts/check_agentmemory.py

OpenClaw Workflow

1. Add the MCP server:

openclaw mcp set agentmemory '{"command":"'"$HOME"'/.local/bin/agentmemory","args":["mcp"],"env":{"AGENTMEMORY_URL":"http://localhost:3111","AGENTMEMORY_TOOLS":"all"}}'

2. Install or link the OpenClaw memory plugin from a durable directory, not a temporary source checkout.
3. Ensure plugins.slots.memory is agentmemory, plugins.entries.agentmemory.enabled is true, and the plugin config includes base_url, token_budget, min_confidence, fallback_on_error, and timeout_ms.
4. Verify with:

openclaw mcp show agentmemory
openclaw plugins inspect agentmemory
openclaw plugins doctor

Edge-Case Rules

• Treat MCP fallback mode as degraded: it exposes only a small local tool set when the REST server is unreachable. Start the server for the full tool surface.
• For sandboxed agents, localhost may point inside the sandbox. Use a reachable host route and AGENTMEMORY_FORCE_PROXY=1 only when the route is correct.
• Never send AGENTMEMORY_SECRET over non-loopback http://. Prefer HTTPS or SSH tunneling; set AGENTMEMORY_REQUIRE_HTTPS=1 for hard failure.
• Re-run agentmemory connect codex --with-hooks after upgrading AgentMemory because user-scope hooks contain absolute script paths.
• Remove duplicate OpenClaw plugin paths; stale temp paths can shadow durable installs.
• Use AGENT_ID and AGENTMEMORY_AGENT_SCOPE=isolated only when roles need strict separation. Default shared memory is usually better for one user's coding agents.
• Keep AGENTMEMORY_INJECT_CONTEXT=false and AGENTMEMORY_AUTO_COMPRESS=false unless the user explicitly accepts token spend.
• Do not use memory_governance_delete or the /forget workflow without explicit confirmation.

ClawHub-Ready Skill Work

For a skill intended for ClawHub, keep SKILL.md concise, declare OpenClaw runtime requirements in metadata.openclaw, avoid paid-skill/licensing claims, and include a --clawscan-note when publishing because this workflow intentionally configures local binaries, MCP, and network access. Use references/platform-recipes.md before publishing or reviewing the bundle.