Memory Vault
Local-first AI memory layer with hybrid search. Postgres + pgvector. Self-hosted, MIT.
MCP-Server · von MihaiBuilds
Überblick
Memory Vault ist ein MCP-Server von MihaiBuilds. Marktplätze, die wir lesen und die es listen: 1 (Official MCP Registry). Wir haben es erstmals am 2026-10-11 gesehen und seither keine Änderung erfasst. Stand unseres Marktplatz-Durchlaufs vom 2026-10-11.
Was es abfragt
- Läuft auf Ihrem Rechner
- Geheimnisse: 1
- Einstellungen: 5
Was es deklariert, abfragt und ausführt, vollständig
Installieren Sie nur Plugins von Entwicklern, denen Sie vertrauen. Wir zeigen, was die Marktplätze veröffentlichen, und testen keine Plugins.
Verbinden
Befehle und Konfigurationen nur aus den Angaben der Marktplätze. Wir führen sie nicht für Sie aus und testen keine Plugins.
Als lokaler MCP-Server: Docker-Image
Erstellt aus den Angaben von Official MCP Registry.
claude mcp add --env "DB_HOST=<YOUR_DB_HOST>" --env "DB_NAME=<YOUR_DB_NAME>" --env "DB_PASSWORD=<YOUR_DB_PASSWORD>" --env "DB_PORT=<YOUR_DB_PORT>" --env "DB_USER=<YOUR_DB_USER>" --transport stdio memory-vault -- docker run -i --rm -e DB_HOST -e DB_NAME -e DB_PASSWORD -e DB_PORT -e DB_USER ghcr.io/mihaibuilds/memory-vault-mcp:1.6.1[mcp_servers.memory-vault]
command = "docker"
args = ["run", "-i", "--rm", "-e", "DB_HOST", "-e", "DB_NAME", "-e", "DB_PASSWORD", "-e", "DB_PORT", "-e", "DB_USER", "ghcr.io/mihaibuilds/memory-vault-mcp:1.6.1"]
[mcp_servers.memory-vault.env]
DB_HOST = "<YOUR_DB_HOST>"
DB_NAME = "<YOUR_DB_NAME>"
DB_PASSWORD = "<YOUR_DB_PASSWORD>"
DB_PORT = "<YOUR_DB_PORT>"
DB_USER = "<YOUR_DB_USER>"{
"mcpServers": {
"memory-vault": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"DB_HOST",
"-e",
"DB_NAME",
"-e",
"DB_PASSWORD",
"-e",
"DB_PORT",
"-e",
"DB_USER",
"ghcr.io/mihaibuilds/memory-vault-mcp:1.6.1"
],
"env": {
"DB_HOST": "<YOUR_DB_HOST>",
"DB_NAME": "<YOUR_DB_NAME>",
"DB_PASSWORD": "<YOUR_DB_PASSWORD>",
"DB_PORT": "<YOUR_DB_PORT>",
"DB_USER": "<YOUR_DB_USER>"
}
}
}
}docker run -i --rm -e "DB_HOST=<YOUR_DB_HOST>" -e "DB_NAME=<YOUR_DB_NAME>" -e "DB_PASSWORD=<YOUR_DB_PASSWORD>" -e "DB_PORT=<YOUR_DB_PORT>" -e "DB_USER=<YOUR_DB_USER>" ghcr.io/mihaibuilds/memory-vault-mcp:1.6.1Ersetzen Sie die Werte in spitzen Klammern durch Ihre eigenen. Wir zeigen die Namen der Einstellungen, nie Werte.
Startargumente speichern wir nicht. Braucht der Server welche, nennt sie seine eigene Dokumentation.
Wo es veröffentlicht ist
| Marktplatz | Status | Version | Zahlen | Verifiziert | Erstmals gesehen |
|---|---|---|---|---|---|
| Official MCP Registry (Eintrag in der Registry öffnen) | Gelistet | 1.6.1 | Forks (GitHub): 14 Sterne (GitHub): 65 |
Nicht markiert |
Jede Zahl stammt vom jeweiligen Marktplatz und wird nie über Marktplätze hinweg addiert. Ein Marktplatz ohne veröffentlichte Zahl zeigt keine: keine Zahl ist nicht null.
Was sich geändert hat
Bei diesem Plugin hat sich nichts bewegt, seit wir es beobachten.
Ähnliche Plugins
Produkte, deren eigene Namen, Beschreibungen, Werkzeuge und Skills diesem der Bedeutung nach am nächsten sind, auf allen Marktplätzen, die wir lesen. Die Nähe ist nur innerhalb dieser Liste geordnet.
-
Persistent memory for AI assistants with semantic search and knowledge graph relationships.
-
memtomem io.github.memtomem/memtomem
Markdown-first long-term memory for AI agents. Hybrid BM25 + vector search, runs locally.
-
memforge-memory io.github.volsier/memforge-memory
Team engineering memory for AI coding assistants. 47 MCP tools, pgvector semantic search.
-
mem0 io.github.mem0ai/mem0
Persistent memory for AI agents: add, search, update, and delete long-term memories.
-
Shared memory for AI agents, as a graph in your own Postgres. Writes never call an LLM.
-
Portable AI memory shared across models and harnesses - plain markdown you own.
-
Memory database for LLM agents — persistent semantic + keyword memory, project namespacing, served o
-
mnemo io.github.n24q02m/mnemo
Persistent AI memory with hybrid search and embedded sync. Open, free, unlimited.
-
ai-memory io.github.alphaonedev/ai-memory
Persistent memory for any AI — zero token cost until recall
-
nexsus io.github.dbnexsus/nexsus
Private persistent memory for Claude, ChatGPT & Gemini via MCP - semantic search, zero-code setup.
Ähnliche Plugins nach Marktplatz
Dieselbe Frage an jeden Marktplatz einzeln: Gibt es dort ein Gegenstück zu diesem Plugin?
Gelistet auf Claude Code: claude-plugins-community (5)
-
agent-knowledge io.github.keshrath/agent-knowledge
Cross-session memory for AI agents - knowledge graph, scoring, semantic search
-
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…
-
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.
Gelistet auf 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…
-
Zilliz Cloud management plugin with 14 skills covering cluster lifecycle, collection schema, vector search, index tuning, bulk import, RBAC, backups, and monitoring.
-
Agent skills for Qdrant vector search covering scaling, performance optimization, search quality, monitoring, deployment, model migration, version upgrades, and SDK usage across…
-
Build multimodal AI applications with Pixeltable -- tables, computed columns, embedding search, UDFs, tool-calling agents, and 25+ AI provider integrations.
-
Easily deploy managed PostgreSQL (pg), Kafka, OpenSearch, Clickhouse and other databases, streaming and apps. Free tier available, up and running in minutes.
Gelistet auf 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…
-
Build multimodal AI applications with Pixeltable -- tables, computed columns, embedding search, UDFs, tool-calling agents, and 25+ AI provider integrations.
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
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…
-
Sanity content platform integration with MCP server, agent skills, and slash commands. Query and author content, build and optimize GROQ queries, design schemas, and set up Visual…
Gelistet auf Codex: openai-curated (openai/plugins) (5)
-
Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces…
-
Build with OpenAI APIs, Agents SDK, and ChatGPT Apps, and create and save OpenAI API keys from Codex.
-
Manage Supabase projects directly through ChatGPT. Execute SQL queries on PostgreSQL databases, design and modify table schemas, deploy serverless edge functions, and configure…
-
Cloudflare platform plugin with curated skills for Workers, Wrangler, and Agents SDK plus the official Cloudflare API MCP server.
-
Evaluate Codex skills and plugins from chat with a beginner-friendly start command, local-first reports, token budget explanations, and guided benchmarking.
Gelistet auf Community GitHub marketplaces (5)
-
Easily deploy managed PostgreSQL (pg), Kafka, OpenSearch, Clickhouse and other databases, streaming and apps. Free tier available, up and running in minutes.
-
Create and retrieve from a Foundry IQ knowledge base using File, Azure Blob, or ADLS Gen2, then connect an existing Prompt or Hosted Agent.
-
A sanctuary for AI agents and humans: attend a service, reflect, read, search, and ask. No auth.
-
Expert assistant for Azure Cosmos DB — data modeling, query optimization, performance tuning, and best practices.
-
Build, deploy, and operate AI agents on AWS. Skills for scaffolding agents with Amazon Bedrock AgentCore, connecting tools, memory, policies, evaluation, debugging, and production…
Gelistet auf 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.
-
Explore and query TimeBase streams, schemas, QQL, symbols, and server status via MCP.
-
Safe BLE diagnostics, evidence workflows, and guarded automation for AI agents.
-
Three-layer verification pipeline for AI output. Extracts claims, finds sources, and flags hallucination risks so humans can verify before acting.
-
Skills and interactive Copilot canvas for designing, configuring, testing and deploying agents to Microsoft Foundry.
Gelistet auf Copilot CLI: github/copilot-plugins (5)
-
Toolkit for building Microsoft 365 Copilot declarative agents — scaffolding, JSON manifest development, and capability configuration.
-
workiq
Query Microsoft 365 data with natural language — emails, meetings, documents, Teams messages, and more.
-
Build Power Apps Canvas Apps using the Canvas Authoring MCP server.
-
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…
-
Bring Azure DevOps work-item, repository, and pull-request workflows into GitHub Copilot.
Gelistet auf 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.
-
Fan large tasks out across parallel cloud agents with planners, workers, verifiers, and structured handoffs.
-
Build apps, scripts, and automations with the TypeScript SDK.
-
Iterative self-referential AI loops using the Ralph Wiggum technique.
Gelistet auf Docker MCP Catalog (5)
-
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.
-
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.
-
Discover and connect to a curated marketplace of MCP servers for extending AI agent capabilities.
Gelistet auf Official MCP Registry (5)
-
Persistent memory for AI assistants with semantic search and knowledge graph relationships.
-
memtomem io.github.memtomem/memtomem
Markdown-first long-term memory for AI agents. Hybrid BM25 + vector search, runs locally.
-
memforge-memory io.github.volsier/memforge-memory
Team engineering memory for AI coding assistants. 47 MCP tools, pgvector semantic search.
-
mem0 io.github.mem0ai/mem0
Persistent memory for AI agents: add, search, update, and delete long-term memories.
-
Shared memory for AI agents, as a graph in your own Postgres. Writes never call an LLM.
Nach Bedeutung gefunden, nicht über gemeinsamen Code oder ein gemeinsames Repository: Ähnliche Plugins bleiben getrennte Produkte, und dies ist weder eine Bewertung noch eine Empfehlung.
Ist das Ihr Plugin?
Weisen Sie nach, dass Sie das Plugin pflegen: mit einer Datei im Repository, einer Datei auf Ihrer Domain oder einem DNS-Eintrag. Sie erhalten Hinweise, wenn ein Marktplatz es aufnimmt, entfernt, das Verifiziert-Zeichen oder die angeforderten Angaben ändert, und können den Remote-Endpunkt als Webdienst überwachen lassen.
Daten von Official MCP Registry. Die Zahlen stammen aus unseren eigenen regelmäßigen Durchläufen über die Marktplätze, zuletzt abgerufen am . Kontaktdaten von Plugin-Herausgebern veröffentlichen wir nicht.