広告掲載
MCP.so
ログイン

Memra MCP Server

@usememra

リポジトリ

基本情報

カテゴリ

メモリとナレッジ

トランスポート

stdio

認証方式

oauth

作者

usememra

投稿者

vonsensey

Memra MCP Server について

Memra MCP server — persistent memory for AI agents. EU-hosted, privacy-first, sub-100ms hybrid recall.

Memra MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "memra": {
      "url": "https://usememra.com/mcp",
      "headers": {
        "Authorization": "Bearer memra_live_YOUR_KEY"
      }
    }
  }
}

Memra MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

このサーバーは認証が必要です。ツールの取得にはログインや提供元の認証情報が必要な場合があります。

上のボタンでサーバーのエンドポイントに接続し、ツール一覧を取得できます。

概要

What is Memra?

Memra is a remote MCP (Model Context Protocol) server providing persistent memory for AI agents, hosted in Helsinki (EU). It offers privacy-first, deterministic recall in under 100ms with no LLM in the hot path, and has a free tier with no credit card requirement.

How to use Memra?

Obtain an API key at usememra.com, then configure Memra as an MCP server in your client. For Claude Code use claude mcp add --transport http memra https://usememra.com/mcp --header "Authorization: Bearer memra_live_YOUR_KEY". For Cursor, Cline, or any MCP client, add the endpoint and auth header to your mcp.json file.

Key features of Memra

  • memra_remember / memra_recall for storing and retrieving facts with hybrid semantic + lexical search
  • Write-time contradiction detection: storing a conflicting fact returns conflicts[]
  • Read-your-writes with revision tokens and wait_for_revision for deterministic recall
  • memra_supersede and memra_history for full audit trails when memories are retired
  • Staleness signals (staleness_score / last_confirmed) on every result
  • Token-budget recall via max_tokens to fit context windows
  • memra_bootstrap for priority context at session start
  • Multi-tenant namespaces, PII masking (7 EU languages), and read-only scoped keys

Use cases of Memra

  • Give AI agents persistent memory that survives across conversations and sessions
  • Detect and resolve contradictory facts during storage (e.g., outdated user preferences)
  • Retrieve facts exactly matching identifiers, error codes, or semantics within a token budget
  • Manage memory lifecycle with explicit superseding and history for audit purposes
  • Provide priority context at the start of each session via bootstrap

よくある質問

1

Where is data stored?

Data is hosted in the EU (Helsinki) with a privacy-first approach.

2

Is there a free tier?

Yes, Memra offers a free tier with no credit card required.

3

Can Memra run offline?

Yes, an offline alternative called `memra-local` is available via `pip install memra-local` that uses SQLite and ONNX embeddings with zero cloud calls.

4

What transport protocol does Memra use?

Memra uses Streamable HTTP at the endpoint `https://usememra.com/mcp`.

5

How is authentication handled?

Authentication is done via a Bearer token sent as an HTTP header: `Authorization: Bearer memra_live_YOUR_KEY`.

コメント

「メモリとナレッジ」の他のコンテンツ

Stele

Stele-Dev

Shared memory for AI coding agents. Claude Code, Cursor and Codex read your project's decisions, lessons and tasks before they act.

AOCI-CODE

aoci-spec

Local MCP server and CLI that keeps a Git-versioned, model-written index of a codebase and its database schema, so coding agents start each task with the whole system in view.

1.7K

Neither MCP

stonianua

Project context your AI can query through MCP — with source evidence.

The Cloud

Teka

The Cloud is the AI-native workspace that gives every AI — Claude, ChatGPT, Gemini, and other Frontier & Free or Local models — shared memory and real agents. Not cloud computing: thecloud.so is one workspace where your

UmmahAPI

Yousuf Kazmi

Islamic source data for assistants: Quran, hadith, tafsir, duas, prayer times and qibla. Answers come from real sources with citations instead of recalled text, so verses and hadith are not hallucinated. 36,000+ hadiths

広告掲載