ai-memory v0.8.0

Continue (VS Code / JetBrains) — MCP server + systemMessage

Category 2. Continue supports MCP via ~/.continue/config.json.

Quick install

ai-memory install continue              # dry-run (default)
ai-memory install continue --apply      # write ~/.continue/config.json
ai-memory install continue --uninstall --apply

Handles Part 1 (MCP server registration). Part 2 (systemMessage) is best-effort and still manual.

Part 1 — MCP server

In ~/.continue/config.json:

{
  "experimental": {
    "modelContextProtocolServers": [
      {
        "transport": {
          "type": "stdio",
          "command": "ai-memory",
          "args": ["mcp"],
          "env": {
            "AI_MEMORY_DB": "${HOME}/.claude/ai-memory.db"
          }
        }
      }
    ]
  }
}

Using --tier smart or --tier autonomous with a non-default LLM backend? Post-#1146 (v0.7.0) the recommended path is a [llm] section in ~/.config/ai-memory/config.toml — single source of truth across MCP / HTTP daemon / CLI / boot banner / doctor probe. Example: backend = "xai", model = "grok-4.3", api_key_env = "XAI_API_KEY" (the env-var name, not the literal key — inline keys are rejected at parse time). Export the named env var in your shell rc; the MCP config can stay minimal. Override path: extend the inner env block above with AI_MEMORY_LLM_BACKEND, AI_MEMORY_LLM_API_KEY, and AI_MEMORY_LLM_MODEL — shell exports don’t reach MCP-spawned subprocesses (#1144). Full schema + per-vendor recipes: ../CONFIG_SCHEMA.md + llm-backends.md.

Part 2 — systemMessage (best-effort)

Add to the same config:

{
  "systemMessage": "At the start of every conversation, before responding to the user's first message, call memory_session_start then memory_recall against the project's namespace and reference the recalled titles in your first reply. Default namespace: derived from the current workspace folder."
}

Limitation + better

Same category-2 limitation as Cursor / Cline. Cross-file at Continue upstream tracked in #487.