io.github.volsier/memforge-memory
Team engineering memory for AI coding assistants. 47 MCP tools, pgvector semantic search.
Serveur MCP · par volsier
Aperçu
io.github.volsier/memforge-memory est un serveur MCP publié par volsier. Places de marché que nous lisons et qui le référencent : 1 (Official MCP Registry). Nous l'avons vu pour la première fois le 2026-10-11 et n'avons enregistré aucun changement depuis. Selon notre passage sur les places de marché du 2026-10-11.
Ce qu'il demande
- S'exécute sur votre machine
- Secrets : 1
- Paramètres : 4
Ce qu'il déclare, demande et exécute, en détail
N’installez que des plugins de développeurs en qui vous avez confiance. Nous reprenons ce que publient les places de marché et ne testons pas les plugins.
Connecter
Commandes et configurations construites uniquement à partir de ce que déclarent ses places de marché. Nous ne les exécutons pas pour vous et ne testons pas les plugins.
En serveur MCP local : paquet npm
Construit à partir de ce que déclare Official MCP Registry.
claude mcp add --env "DATABASE_URL=<YOUR_DATABASE_URL>" --env "OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>" --env "OPENAI_BASE_URL=<YOUR_OPENAI_BASE_URL>" --env "OPENAI_EMBEDDING_MODEL=<YOUR_OPENAI_EMBEDDING_MODEL>" --transport stdio memforge-memory -- npx -y @memforgeai/memory-service[mcp_servers.memforge-memory]
command = "npx"
args = ["-y", "@memforgeai/memory-service"]
[mcp_servers.memforge-memory.env]
DATABASE_URL = "<YOUR_DATABASE_URL>"
OPENAI_API_KEY = "<YOUR_OPENAI_API_KEY>"
OPENAI_BASE_URL = "<YOUR_OPENAI_BASE_URL>"
OPENAI_EMBEDDING_MODEL = "<YOUR_OPENAI_EMBEDDING_MODEL>"{
"mcpServers": {
"memforge-memory": {
"command": "npx",
"args": [
"-y",
"@memforgeai/memory-service"
],
"env": {
"DATABASE_URL": "<YOUR_DATABASE_URL>",
"OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>",
"OPENAI_BASE_URL": "<YOUR_OPENAI_BASE_URL>",
"OPENAI_EMBEDDING_MODEL": "<YOUR_OPENAI_EMBEDDING_MODEL>"
}
}
}
}Remplacez les valeurs entre chevrons par les vôtres. Nous montrons les noms des paramètres, jamais de valeurs.
Nous ne gardons pas les arguments de lancement. Si le serveur en demande, sa propre documentation les donne.
Où il est publié
| Place de marché | Statut | Version | Chiffres | Vérifié | Vu pour la première fois |
|---|---|---|---|---|---|
| Official MCP Registry (Ouvrir la fiche du registre) | Référencé | 1.0.1 | Aucun chiffre publié | Non marqué |
Chaque chiffre est celui de la place de marché et n'est jamais additionné entre places de marché. Une place de marché qui ne publie pas de chiffre n'en affiche aucun : pas de nombre ne veut pas dire zéro.
Ce qui a changé
Rien n'a bougé sur ce plugin depuis que nous le suivons.
Plugins similaires
Produits dont les noms, descriptions, outils et skills sont les plus proches de celui-ci par le sens, sur toutes les places de marché que nous lisons. La proximité n'est classée qu'à l'intérieur de cette liste.
-
cogmem io.github.writerslogic/cogmem
A self-improving, verifiable memory layer for AI coding agents.
-
memory io.github.shackleai/memory
Persistent memory for AI coding tools. 11 tools for any MCP-compatible AI tool.
-
Persistent memory layer for AI coding agents — your agent remembers what you taught it.
-
Graph-vector memory for AI assistants using FalkorDB and Qdrant
-
Local-first AI memory layer with hybrid search. Postgres + pgvector. Self-hosted, MIT.
-
Local-first long-term memory for AI coding agents. Stored on your own machine.
-
mem0 io.github.mem0ai/mem0
Persistent memory for AI agents: add, search, update, and delete long-term memories.
-
memtomem io.github.memtomem/memtomem
Markdown-first long-term memory for AI agents. Hybrid BM25 + vector search, runs locally.
-
Adaptive memory for AI agents — FAISS search, chat extraction, cross-project linking
-
SAME - Stateless Agent Memory Engine
Persistent memory for AI coding agents. Local-first SQLite + vector search. 17 MCP tools.
Plugins similaires par place de marché
La même question posée à chaque place de marché séparément : y a-t-il là un équivalent de ce plugin ?
Référencé sur Claude Code: claude-plugins-community (5)
-
Persistent semantic memory for Claude Code. Stores knowledge in a local ChromaDB vector database and automatically retrieves relevant context on every message using Ollama bge-m3…
-
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…
-
Persistent local memory for Claude Code — cross-session context, semantic search, zero cloud
-
Persistent memory for AI coding agents. SQLite knowledge graph with scoped entities, MCP tools, and LLM-summarized briefings.
-
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…
Référencé sur Claude Code: claude-plugins-official (5)
-
Pinecone vector database integration. Streamline your Pinecone development with powerful tools for managing vector indexes, querying data, and rapid prototyping. Use slash…
-
Precise local semantic code search via MCP. Indexes your codebase with Go AST parsing, embeds with Ollama or LM Studio, and exposes vector search to Claude through an MCP server…
-
Agent skills for Qdrant vector search covering scaling, performance optimization, search quality, monitoring, deployment, model migration, version upgrades, and SDK usage across…
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
Build multimodal AI applications with Pixeltable -- tables, computed columns, embedding search, UDFs, tool-calling agents, and 25+ AI provider integrations.
Référencé sur Claude: knowledge-work-plugins (5)
-
Agent skills for Qdrant vector search covering scaling, performance optimization, search quality, monitoring, deployment, model migration, version upgrades, and SDK usage across…
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
Build multimodal AI applications with Pixeltable -- tables, computed columns, embedding search, UDFs, tool-calling agents, and 25+ AI provider integrations.
-
Atlan data catalog plugin for Claude Code. Search, explore, govern, and manage your data assets through natural language. Powered by the Atlan MCP server with semantic search…
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
Référencé sur Codex: openai-curated (openai/plugins) (5)
-
Build with OpenAI APIs, Agents SDK, and ChatGPT Apps, and create and save OpenAI API keys from Codex.
-
Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces…
-
Evaluate Codex skills and plugins from chat with a beginner-friendly start command, local-first reports, token budget explanations, and guided benchmarking.
-
Manage Supabase projects directly through ChatGPT. Execute SQL queries on PostgreSQL databases, design and modify table schemas, deploy serverless edge functions, and configure…
-
CrowdStrike Falcon Foundry development skills for building cybersecurity applications on the Falcon platform. Includes UI development, collections, functions, workflows, API…
Référencé sur Community GitHub marketplaces (5)
-
Local graph memory that lets Codex recall project context across sessions.
-
bettermemory io.github.0Mattias/bettermemory
Memory for coding agents, checked against the filesystem and git before it is believed.
-
Dash0 Observability
OpenTelemetry observability for OpenAI Codex sessions. Captures prompts, tool calls, MCP calls, sub-agent activity, and token usage as OTel traces.
-
Comprehensive development workflow for building AI agents with the Atomic Agents framework. Includes specialized agents for schema design, architecture planning, code review, and…
-
Create and retrieve from a Foundry IQ knowledge base using File, Azure Blob, or ADLS Gen2, then connect an existing Prompt or Hosted Agent.
Référencé sur Copilot CLI: github/awesome-copilot (5)
-
Run a lightweight, role-separated AI development team with flexible tools, developer-selected models, proportionate planning, and optional QA.
-
Task Researcher and Task Planner for intermediate to expert users and large codebases - Brought to you by microsoft/edge-ai
-
Model, visualize, and deploy applications with Radius from the GitHub Copilot app and CLI.
-
Meta prompts that help you discover and generate curated GitHub Copilot agents, instructions, prompts, and skills.
-
Skills and interactive Copilot canvas for designing, configuring, testing and deploying agents to Microsoft Foundry.
Référencé sur 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.
-
Advanced Security plugin for GitHub Copilot.
-
model-apps
Build and deploy Power Apps generative pages for model-driven apps with specialist agents for planning, entity creation, and parallel code generation. Requires PAC CLI >= 2.7.0…
Référencé sur Cursor: cursor/plugins (5)
-
Incremental transcript-driven memory updates for AGENTS.md using high-signal bullet points only.
-
Iterative self-referential AI loops using the Ralph Wiggum technique.
-
Build apps, scripts, and automations with the TypeScript SDK.
-
Capture, search, and organize notes and collections.
-
Consult a stronger model before major decisions, when stuck, and before declaring done.
Référencé sur Docker MCP Catalog (5)
-
mcp-neo4j-memory io.github.neo4j-contrib/mcp-neo4j-memory
MCP Neo4j Knowledge Graph Memory Server
-
The Official Model Context Protocol (MCP) server for Kagi Search & other tools.
-
Bridges multiple AI models and CLIs, enabling orchestrated workflows across Claude Code, Gemini CLI, Codex CLI, and other AI development tools.
-
A Model Context Protocol (MCP) server implementation that provides database capabilities for Chroma.
-
Production-ready RAG service to search and retrieve data from your documents.
Référencé sur Official MCP Registry (5)
-
cogmem io.github.writerslogic/cogmem
A self-improving, verifiable memory layer for AI coding agents.
-
memory io.github.shackleai/memory
Persistent memory for AI coding tools. 11 tools for any MCP-compatible AI tool.
-
Persistent memory layer for AI coding agents — your agent remembers what you taught it.
-
Graph-vector memory for AI assistants using FalkorDB and Qdrant
-
Local-first AI memory layer with hybrid search. Postgres + pgvector. Self-hosted, MIT.
Trouvés par le sens, et non par un code ou un dépôt commun : les plugins similaires restent des produits distincts, et ceci n'est ni un avis ni une recommandation.
C'est votre plugin ?
Prouvez que vous maintenez ce plugin avec un fichier dans son dépôt, un fichier sur votre domaine ou un enregistrement DNS. Vous recevez des alertes quand une place de marché le publie, le retire, change sa marque vérifiée ou ce qu'il demande, et vous pouvez mettre son endpoint distant sous surveillance comme service web.
Données issues de Official MCP Registry. Les chiffres proviennent de nos propres passages réguliers sur les places de marché, dernière lecture le . Nous ne publions aucune coordonnée des éditeurs de plugins.