Plugin Claude Code
Bundles 18 skills, 1 MCP server · 1,108 tokens together
Persistent, local-first memory for AI agents. Remembers facts, preferences, and decisions across sessions with a bi-temporal knowledge graph, over MCP — runs fully local on SQLite with no mandatory LLM calls. Calibrated prediction & behavior discovery available in hosted mode.
Skill Claude CodeCodex
MemMesh CLI + local MCP server — the zero-infra, no-API-key path to the same engine as the hosted SDK. Runs fully local over SQLite. Covers install (wires MCP config + the teaching skill into Claude Code / Cursor / Windsurf / Codex), and the memory subcommands (save / get / search / migrate / mcp / serve). TRIGGER…
Skill Claude CodeCodex
Integrate MemMesh into an existing repository using a goal-driven, test-first (TDD) pipeline. Detects the repo's language/stack, asks whether to use MemMesh Hosted (SDK, managed) or Local (CLI + MCP over SQLite), writes failing tests before any implementation, and lands additive, feature-flag-gated code that a…
Skill Claude CodeCodex
Migrate an existing memory setup ONTO MemMesh — either from another vendor (Mem0, Zep, Letta/MemGPT, a raw vector store) or from MemMesh Local (SQLite) up to MemMesh Hosted. Audits the current usage, produces a reviewable migration plan (API mapping + data export/import), and executes it on approval. Maps add→observe…
Skill Claude CodeCodex
MemMesh TypeScript SDK reference (@thinkfleet/memory-sdk) for the hosted platform at app.memmesh.ai. Covers the ThinkFleetMemory client — observe / search / list, the predict + lattice prediction surface, closed-loop learning (recordDecision / recordOutcome), emergent behavior discovery, and the health / financial…
Skill Claude CodeCodex
Verify a MemMesh integration produced by memmesh-integrate. Runs in the same workspace: executes the repo's native test suite, then exercises a real end-to-end smoke flow (observe → search → optionally predict) against the user's live key or local engine, and produces a pass/fail scorecard. TRIGGER when: the user has…
Skill Claude CodeCodex
Persistent hierarchical memory shared across every AI tool the user runs. The engine decides what's worth saving — your job is just to feed it raw text via memory.observe and to recall via memory.search when context would help. Use both on every session.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: