memini
Persistent memory for AI coding agents via the memini memory service. 7 hooks, MCP tools, and skills that capture tool usage and inject prior context at session start.
Pacote de plugins · de memini maintainers
Resumo
memini é um pacote de plugins para ferramentas de programação com IA publicado por memini maintainers. Marketplaces que lemos e que o listam: 1 (Community GitHub marketplaces). A última mudança que registramos foi em 2026-10-20. Conforme nossa passagem pelos marketplaces em 2026-10-20.
O que pede
- Instala-se como pacote de plugins
Nenhum dos marketplaces que lemos publica as ferramentas ou as configurações que ele pede.
O que declara, pede e executa, por completo
Instale apenas plugins de desenvolvedores em quem você confia. Mostramos o que os marketplaces publicam e não testamos plugins.
Funciona com
- Claude Code
Pelos marketplaces que o listam e pelo transporte MCP que declara, conforme cada cliente documenta. Não testamos plugins.
Conectar
Comandos e configurações gerados apenas a partir do que os marketplaces declaram. Não os executamos por você e não testamos plugins.
Como plugin do Claude Code
Gerado a partir do que Community GitHub marketplaces declara.
/plugin marketplace add eleboucher/memini
/plugin install memini@memini
Onde está publicado
| Marketplace | Status | Versão | Números | Verificado | Visto pela primeira vez |
|---|---|---|---|---|---|
| Marketplace da comunidade eleboucher/memini (Abrir o código no GitHub) | Listado | 0.7.36 | Forks (GitHub): 9 Estrelas (GitHub): 28 |
Sem marcação |
Cada número é do próprio marketplace e nunca é somado entre marketplaces. Um marketplace que não publica números não mostra nenhum: sem número não é zero.
Listado em um marketplace da comunidade
| Marketplace | Repositório | Estrelas (GitHub) |
|---|---|---|
| memini | eleboucher/memini | 28 |
Como os números mudaram
- 2026-10-1826
- 2026-10-1927
- 2026-10-2028
Cada ponto é um dia em que lemos um número diferente; os trechos planos são dias em que o número não mudou. Números de marketplaces diferentes nunca são somados.
O que o pacote contém
Conforme publicado em Community GitHub marketplaces.
Servidores MCP: 1
memini
Skills: 10
backfilldoctorforgethandoffnamespacepinrecallrecaprememberstatus
Comandos: 9
backfilldoctorforgethandoffnamespacepinrecallrememberstatus
O que mudou
- Passou a ser um produto que acompanhamos
- Community GitHub marketplaces: apareceu
Plugins semelhantes
Produtos cujos próprios nomes, descrições, ferramentas e skills são os mais próximos deste pelo significado, em todos os marketplaces que lemos. A proximidade é ordenada apenas dentro desta lista.
-
Persistent memory system for AI coding sessions — cross-tool memory sharing with hybrid search
-
Persistent memory for AI coding agents. SQLite knowledge graph with scoped entities, MCP tools, and LLM-summarized briefings.
-
Persistent memory layer for AI coding agents — your agent remembers what you taught it.
-
Persistent cross-session memory for Claude Code via Awareness Memory Cloud
-
Coding Agents forget everything when a session ends. total-recall fixes that: a shared memory layer that persists across sessions, tools, and devices. Memory is organized into…
-
Persistent, local-first memory for AI coding agents. Remember, recall and forget across sessions.
-
Git-native project memory for AI coding agents, with deterministic local recall, evidence gates, and layered delivery that quotes, points, or abstains.
-
Persistent memory for Claude Code that survives /clear, machine switches, and team handoffs. Hosted memory backend with hybrid retrieval (vector + BM25 + RRF), Ebbinghaus temporal…
-
yggdrasil io.github.VonderVuflya/yggdrasil
One shared, durable memory for your AI coding agents — local-first, zero-dependency.
-
Persistent, cross-device memory for your AI coding agents — self-hosted and AGPL, so your knowledge never leaves your own infrastructure. Connect to a Mori server you run; every…
Plugins semelhantes por marketplace
A mesma pergunta feita a cada marketplace separadamente: existe lá um equivalente deste plugin?
Listado em Claude Code: claude-plugins-community (5)
-
Persistent memory for AI coding agents. SQLite knowledge graph with scoped entities, MCP tools, and LLM-summarized briefings.
-
Coding Agents forget everything when a session ends. total-recall fixes that: a shared memory layer that persists across sessions, tools, and devices. Memory is organized into…
-
claude-code-plugin-for-goodmem-a-memory-infra-for-agents
With this plugin, you can operate Goodmem's memory infra in plain English, to create, manage, and orchestrate embedders, rerankers, and LLMs, to ingest and create memories from…
-
Local AI memory system for Claude Code and Cursor. Remembers your preferences, decisions, and project context across sessions using a Go HTTP service and Qdrant vector database…
-
engram io.github.tstockham96/engram
Intelligent agent memory with automatic extraction, consolidation, and bi-temporal recall.
Listado em Claude Code: claude-plugins-official (5)
-
Continuous memory for Claude Code. Extracts, summarizes, and compresses conversations into tiered daily logs. Claude remembers what you did yesterday.
-
Comprehensive development workflow for building AI agents with the Atomic Agents framework. Includes specialized agents for schema design, architecture planning, code review, and…
-
Output.ai workflow development toolkit for Claude Code. Adds 5 specialist agents (planner, builder, debugger, prompt writer, quality reviewer), 40+ slash-command skills covering…
-
Generate an explorable HTML report of Claude Code session usage — tokens, cache efficiency, subagents, skills, and the most expensive prompts — from local ~/.claude/projects…
-
Interactive self-referential AI loops for iterative development, implementing the Ralph Wiggum technique. Claude works on the same task repeatedly, seeing its previous work, until…
Listado em Claude: knowledge-work-plugins (5)
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
AI-first project auditor and re-engineer based on the 9 design principles and 7 design patterns from the TechWolf AI-First Bootcamp
-
Streamline engineering workflows — standups, code review, architecture decisions, incident response, and technical documentation. Works with your existing tools or standalone.
-
MCP server for terminal commands, file operations, and process management
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
Listado em Codex: openai-curated (openai/plugins) (5)
-
Build with OpenAI APIs, Agents SDK, and ChatGPT Apps, and create and save OpenAI API keys from Codex.
-
Evaluate Codex skills and plugins from chat with a beginner-friendly start command, local-first reports, token budget explanations, and guided benchmarking.
-
An agentic skills framework & software development methodology that works: planning, TDD, debugging, and collaboration workflows.
-
Notion workflows for implementation planning, research synthesis, meeting preparation, and knowledge capture.
-
Turn Codex into your ClickUp command center.
Listado em Community GitHub marketplaces (5)
-
Persistent memory system for AI coding sessions — cross-tool memory sharing with hybrid search
-
Persistent cross-session memory for Claude Code via Awareness Memory Cloud
-
Git-native project memory for AI coding agents, with deterministic local recall, evidence gates, and layered delivery that quotes, points, or abstains.
-
Persistent memory for Claude Code that survives /clear, machine switches, and team handoffs. Hosted memory backend with hybrid retrieval (vector + BM25 + RRF), Ebbinghaus temporal…
-
yggdrasil io.github.VonderVuflya/yggdrasil
One shared, durable memory for your AI coding agents — local-first, zero-dependency.
Listado em Copilot CLI: github/awesome-copilot (5)
-
Meta prompts that help you discover and generate curated GitHub Copilot agents, instructions, prompts, and skills.
-
Run a lightweight, role-separated AI development team with flexible tools, developer-selected models, proportionate planning, and optional QA.
-
Goal-driven task orchestration with independent verification. Interviews the user to define a clear goal, then loops between a Builder subagent (does the work) and an Inspector…
-
Task Researcher and Task Planner for intermediate to expert users and large codebases - Brought to you by microsoft/edge-ai
-
Shows live prompt-cache reuse, expiry, token composition, and AI Credit cost for the current GitHub Copilot session without making model calls.
Listado em Copilot CLI: github/copilot-plugins (5)
-
Toolkit for building Microsoft 365 Copilot declarative agents — scaffolding, JSON manifest development, and capability configuration.
-
Bring Azure DevOps work-item, repository, and pull-request workflows into GitHub Copilot.
-
workiq
Query Microsoft 365 data with natural language — emails, meetings, documents, Teams messages, and more.
-
workiq-productivity
WorkIQ productivity skills powered by the local WorkIQ CLI — read-only insights across email, meetings, calendar, Teams, SharePoint, projects, and people.
-
Build and manage Microsoft Dataverse solutions using natural language. Includes table/column creation, solution lifecycle, data operations, and MCP server configuration.
Listado em Cursor: cursor/plugins (5)
-
Incremental transcript-driven memory updates for AGENTS.md using high-signal bullet points only.
-
Capture, search, and organize notes and collections.
-
Iterative self-referential AI loops using the Ralph Wiggum technique.
-
Consult a stronger model before major decisions, when stuck, and before declaring done.
-
Build apps, scripts, and automations with the TypeScript SDK.
Listado em Docker MCP Catalog (5)
-
A Model Context Protocol server for Omi interaction and automation. This server provides tools to read, search, and manipulate Memories and Conversations.
-
mcp-neo4j-memory io.github.neo4j-contrib/mcp-neo4j-memory
MCP Neo4j Knowledge Graph Memory Server
-
Stop stitching context for Copilot and Cursor. With Sequa MCP, your AI tools know your entire codebase and docs out of the box.
-
Bridges multiple AI models and CLIs, enabling orchestrated workflows across Claude Code, Gemini CLI, Codex CLI, and other AI development tools.
-
Production-ready RAG service to search and retrieve data from your documents.
Listado em Official MCP Registry (5)
-
Persistent memory layer for AI coding agents — your agent remembers what you taught it.
-
Persistent, local-first memory for AI coding agents. Remember, recall and forget across sessions.
-
yggdrasil io.github.VonderVuflya/yggdrasil
One shared, durable memory for your AI coding agents — local-first, zero-dependency.
-
Shared, project-aware memory for Claude Code, Codex, and other agents with human review.
-
Local-first long-term memory for AI coding agents. Stored on your own machine.
Listado em npm registry (MCP servers) (5)
-
Local persistent memory and Markdown wiki for AI coding agents: 24 MCP tools, no gateway required.
-
One workspace for every AI coding assistant. Shared tasks, memory, and governance.
-
Discover and load Agent Skills from configured local directories and Git sources over stdio MCP.
-
easy-notion io.github.misterwigglesworth/easy-notion
Markdown-first Notion MCP server. ~6-7x fewer response tokens vs official Notion MCP. 43 tools.
-
dav-mcp io.github.PhilflowIO/dav-mcp
AI-orchestrated calendars, contacts & tasks across any DAV platform. 27 tools, field-agnostic.
Encontrados pelo significado, não por código ou repositório em comum: plugins semelhantes continuam sendo produtos distintos, e isto não é uma avaliação nem uma recomendação.
Quer esta marca no seu plugin em nosso catálogo?
Prove que o mantém com um arquivo no repositório, um arquivo no seu domínio ou um registro DNS, e você poderá mostrar esta marca na ficha, com banners ao vivo para o seu site e o README. Como funciona a verificação
Você também recebe alertas quando um marketplace o publica, o remove, muda a marca de verificado ou o que ele pede, e o endpoint remoto passa a ser monitorado como um serviço web.
Dados de Community GitHub marketplaces. Os números vêm das nossas próprias passagens regulares pelos marketplaces, última leitura em . Não publicamos dados de contato dos editores de plugins.