thinkfleetai/memmesh/memmesh-cli

MemMesh CLI

The CLI drives the same Rust engine as the hosted platform, but fully local over SQLite — no account, no key, no network. It is also the recommended way to give any MCP-capable agent persistent memory.

Install (one command, multi-tool)

npx @thinkfleet/memmesh install        # or: memmesh install

This auto-detects your installed AI tools and, for each, writes the MCP server config and drops the teaching skill:

• Claude Code (~/.claude.json + ~/.claude/skills/)
• Cursor (~/.cursor/mcp.json)
• Windsurf
• Codex CLI

Useful flags: --dry-run (preview), --tool <name> (one tool only), --skill-only / --mcp-only, --force (overwrite existing config).

Verify wiring at any time:

memmesh doctor        # checks binary, MCP config, skill presence, hooks

Memory subcommands

memmesh save --type preference --scope user --content "prefers pnpm over npm"
memmesh get <id>
memmesh search --project myapp --query "database"        # substring/scoped search
memmesh list  --project myapp --limit 20
memmesh migrate                                          # run pending DB migrations

Run the MCP server

Most agents launch this for you via the config the installer wrote. To run it by hand (stdio JSON-RPC 2.0):

memmesh mcp

The server exposes 15 tools — see the memmesh skill for the full list and the observe/recall usage pattern. Highlights beyond basic CRUD: memory_predict, memory_build_context, memory_graph_reason, memory_query_graph, memory_prefetch_related, plus the client-LLM graph extraction pair (memory_extract_pending / memory_commit_extraction) — the engine never makes LLM calls; your agent's own model does the extraction.

Local vs hosted

Free tier caps local storage at 500 items (free_tier.entry_cap in ~/.thinkfleet-memory/config.toml).

Config

~/.thinkfleet-memory/config.toml holds the sync URL, JWT token, and tier caps. Point sync.url at your hosted mesh to push local memory up; leave it unset to stay fully offline.