GoodMem Claude Code Plugin

A Claude Code plugin for GoodMem — memory infrastructure for AI agents.

With this plugin, you can operate GoodMem's memory infrastructure in plain English — create and manage embedders, rerankers, and LLMs, ingest memories from files, base64 strings, and plain text, and build knowledge-powered agents for RAG and Deep Research. Also includes Python and Java SDK references for writing GoodMem code.

Use cases

Deep Research agent — Create an embedder and space, ingest research papers and documents, then ask complex questions that retrieve and synthesize information across your entire knowledge base.
RAG pipeline — Configure embedders, rerankers, and LLMs, store source materials as memories, and retrieve relevant context for answering questions.
Self-improving support agent — Ingest historical issue tickets and resolutions, search for solutions matching a new problem description, and iteratively store new discoveries and fixes as memories so future troubleshooting gets smarter over time.

Installation

From the community marketplace (preferred):

/plugin marketplace add anthropics/claude-plugins-community
/plugin install goodmem@claude-community

From this repo (fallback — use only if the community marketplace is unavailable):

/plugin marketplace add PAIR-Systems-Inc/goodmem-claude-code-plugin
/plugin install goodmem@goodmem-plugins

Configuration

What you need to configure

GoodMem credentials (required):

GOODMEM_BASE_URL — GoodMem server URL (e.g., https://your-server.example.com)
GOODMEM_API_KEY — GoodMem API key (starts with gm_)

TLS / self-signed certificates (optional):

If the server uses a private or self-signed CA, set NODE_EXTRA_CA_CERTS to the absolute path of its PEM certificate file before launching Claude Code. Restart the MCP connection after changing this setting. An expired or invalid server certificate must be fixed on the server.

How to configure

1. In English from chat (GoodMem credentials only; TLS variables cannot be set this way)

Just tell Claude your server details — it will call goodmem_configure automatically:

> "Configure GoodMem with base URL https://my-server.com and API key gm_abc123"

Credentials persist for the session. You can reconfigure anytime to switch servers.

2. Shell export (before launching Claude Code; works for all configurations)

export GOODMEM_BASE_URL="https://your-server.example.com"
export GOODMEM_API_KEY="gm_..."
export NODE_EXTRA_CA_CERTS="/path/to/rootCA.pem"  # only if needed for self-signed certs

Reloading after updates

After installing a new version or pulling the latest changes, run /reload-plugins inside Claude Code to pick up the updates without restarting. If you are using the plugin from this repo, you can run git pull to get the latest changes.

What's included

Component	Description
`skills/help/`	Setup guide, available skills overview, example workflows
`skills/python/`	Python SDK reference — method signatures, parameters, examples
`skills/java/`	Java SDK usage reference — setup, builders, streaming, pagination, examples
`skills/mcp/`	MCP workflow guide; tool discovery provides current parameters
`.mcp.json`	MCP server with auto-inference from the built-in model registry

Skills

goodmem:help — Overview of all skills, setup instructions, example workflows
goodmem:python — Python SDK reference for writing GoodMem code
goodmem:java — Java SDK reference for writing GoodMem code
goodmem:mcp — MCP tools reference for direct operations

MCP tools

The MCP server exposes all GoodMem API operations as tools:

goodmem_configure — set server credentials from chat
goodmem_lookup_model — look up model info from the built-in registry
embedders — create, list, get, update, delete embedding models
llms — create, list, get, update, delete LLM configurations
rerankers — create, list, get, update, delete reranker models
spaces — create, list, get, update, delete memory spaces
memories — create, list, get, update, delete, retrieve, batch operations
ocr — extract text from documents
users, apikeys, system, admin — manage users, API keys, server

Auto-inference

When creating embedders, LLMs, or rerankers, just provide model_identifier and the plugin auto-fills provider, endpoint, dimensions, and other fields from the built-in model registry. You only need to provide display_name, model_identifier, and credentials — everything else is inferred.

Explicit values always override inferred defaults.

Credential validation

SaaS providers (OpenAI, Cohere, Voyage, Jina, and OpenAI-compatible endpoints for Anthropic, Google, Mistral) require API credentials. If you create an embedder, LLM, or reranker pointing at a known SaaS hostname without providing credentials, the plugin raises a clear error before the request reaches the server. Pass credentials (MCP), api_key (Python SDK), or the provider API key overload (Java SDK) to proceed.

goodmem-claude-code-plugin