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...

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

When To Use

Use this skill when the user wants to install AgentMemory, wire AgentMemory MCP into Codex or OpenClaw, audit an existing memory setup, publish AgentMemory guidance to ClawHub, or debug memory failures involving npx, localhost routing, bearer-token safety, stale hooks, duplicate plugin paths, or degraded MCP fallback mode.

Operating Order

1. Confirm the target surface: Codex, OpenClaw, ClawHub skill packaging, or a specific project workspace.
2. Read the bundled references for current architecture and platform-specific recipes.
3. Prefer a pinned local AgentMemory binary over long-lived npx commands.
4. Apply the narrowest config change that satisfies the target surface, preserving existing user settings.
5. Run the diagnostic script before and after changes, then explain any warnings as operational risks rather than hiding them.
6. For public skill work, run Codex quick validation, ClawHub skill doctor, leak/prompt-bleed scans, ClawPatch review, and a gstack-style ship gate before publishing.

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:

bash

npm install --prefix ~/.agentmemory/npm @agentmemory/agentmemory@0.9.22 --omit=optional
mkdir -p ~/.local/bin
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:

bash

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:

bash

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:

bash

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

OpenClaw Workflow

1. Add the MCP server:

bash

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:

bash

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.