paddleocr
Reads text from scanned pages, photos and PDFs and returns it as structured Markdown or JSON, so you can pull tables, formulas and headers out of a document without retyping them. Covers many languages and works as input for AI tools.
Gives Claude Code a long-term memory layer with semantic search, recall injection, and graph entities, letting agents recall, save, inspect, and audit memories through bundled MCP tools.
Claude Code
$ npx -y skills add NeoLi00/memX --agent claude-code
Codex
$ npx skills add NeoLi00/memX -a codex
Cursor
$ npx skills add NeoLi00/memX -a cursor
Gemini CLI
$ npx skills add NeoLi00/memX -a gemini-cli
GitHub Copilot
$ npx skills add NeoLi00/memX -a github-copilot
OpenCode
$ npx skills add NeoLi00/memX -a opencode
Windsurf
$ npx skills add NeoLi00/memX -a windsurf
English ยท ไธญๆ ยท Architecture
memX turns completed work into structured, searchable, self-maintained memory, then injects only the evidence an agent needs for the current query. It connects natively to Codex, Claude Code, and OpenClaw, and reaches any MCP-compatible client through the same local memory layer.
Requirements: Node.js 22.14+ or Node 24. OpenClaw installs require OpenClaw 2026.3.25+. Python 3 is needed only for the default local embedding runtime.
The README commands use the GitHub package spec. A fresh run pulls current GitHub code, so installs
do not wait for an npm publish. To use the npm release channel later, replace
github:NeoLi00/memX with @neoli00/memx.
Fill in these values before running a command:
--llm-provider: the provider adapter memX should call. Choose one of openai-compatible,
anthropic, google, or ollama.--llm-base-url: the base URL for that provider. Examples: https://api.openai.com/v1,
https://api.anthropic.com/v1, https://generativelanguage.googleapis.com/v1beta, or
http://127.0.0.1:11434 for Ollama.--llm-model: the model memX uses for memory compilation, recall planning, and maintenance.
Pick a fast, low-cost model with reliable JSON output.--llm-api-key: the API key for the provider. Use --llm-api-key-env PROVIDER_API_KEY if you
want the config to reference an environment variable instead of storing plaintext. For local
Ollama, omit the key.The default embedding setup is local sentence-transformers-local with
intfloat/multilingual-e5-small. Add --embedding-provider and --embedding-model only when you
want to override that default. Use --dry-run to preview the files and exec-form commands before
writing anything.
For Codex and Claude Code, native hooks are the default lifecycle path for automatic recall and
turn capture. Quickstart installs the native plugin, writes the shared memX config, starts or
refreshes the managed local memX service, and keeps MCP memory tools hidden with --mcp-tools none
by default. This prevents duplicate recall/write and prevents the agent from reading audit data as a
side channel. Use --mcp-tools full only when you intentionally want the agent to see the complete
MCP tool set. Generic MCP quickstart stays full by default because it has no native lifecycle
hooks. Default native memories are also host-scoped, so Codex and Claude Code do not share the same
local database unless you deliberately override the database path and actor settings.
If http://127.0.0.1:3878 is already used by an unmanaged memX-compatible service, quickstart stops
instead of silently reusing it. Stop the old service or pass a free local URL, for example
--memx-url http://127.0.0.1:3888.
This installs the shared memX config, a local Claude Code plugin marketplace, native lifecycle hooks, and the managed local memX service in one run.
npx -y -p github:NeoLi00/memX memx quickstart claude-code \
--llm-provider openai-compatible \
--llm-base-url https://llm.example.com/v1 \
--llm-model fast-memory-model \
--llm-api-key sk-your-provider-key
This installs the shared memX config, a local Codex plugin marketplace, native lifecycle hooks, and the managed local memX service in one run.
npx -y -p github:NeoLi00/memX memx quickstart codex \
--llm-provider openai-compatible \
--llm-base-url https://llm.example.com/v1 \
--llm-model fast-memory-model \
--llm-api-key sk-your-provider-key
npx -y -p github:NeoLi00/memX memx quickstart openclaw \
--llm-provider openai-compatible \
--llm-base-url https://llm.example.com/v1 \
--llm-model fast-memory-model \
--llm-api-key sk-your-provider-key
Use this path for MCP clients that do not have a native memX lifecycle adapter. Quickstart writes the shared memX config, starts the managed local memX service, and prints a ready-to-copy MCP server config.
npx -y -p github:NeoLi00/memX memx quickstart mcp \
--llm-provider openai-compatible \
--llm-base-url https://llm.example.com/v1 \
--llm-model fast-memory-model \
--llm-api-key sk-your-provider-key
npx -y -p github:NeoLi00/memX memx service status
npx -y -p github:NeoLi00/memX memx service restart
npx -y -p github:NeoLi00/memX memx service stop
Use the same --home, --memx-url, and --memx-secret values that you used during quickstart when
you manage a non-default install.
Each uninstall command backs up the target config first, then removes only memX-owned entries.
Claude Code and Codex cleanup also stop the managed local service, uninstall the native plugin,
remove the local marketplace, and delete the generated marketplace snapshot.
OpenClaw cleanup also removes stale memx / memory-memx slot, allow, and entry references, then
best-effort uninstalls both current and legacy plugin files if OpenClaw can still see them.
npx -y -p github:NeoLi00/memX memx uninstall openclaw
npx -y -p github:NeoLi00/memX memx uninstall codex
npx -y -p github:NeoLi00/memX memx uninstall claude-code
Add --dry-run to preview, or --config /path/to/config when using a non-default config path.
Reads text from scanned pages, photos and PDFs and returns it as structured Markdown or JSON, so you can pull tables, formulas and headers out of a document without retyping them. Covers many languages and works as input for AI tools.
Gives your AI assistant a memory that persists across sessions, so it remembers your preferences and earlier work in this repository instead of starting fresh. Search, forget, pause and resume memories with simple commands.
Gives AI agents a library of ready-made skills for scientific work such as metabolic flux analysis, protein experiment design, time series modeling, and analytical method validation, so research tasks need less hand-built code. It works with any agent that supports the open Agent Skills standard.
Gives Claude Code skills, agents, and commands for PostHog analytics, session replay, feature flags, error tracking, and LLM observability. Includes MCP server setup and project access checks.
Install it with the command on its page. It includes memx. Its skills do not fire on their own yet. Free and open source.
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