mcpField
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Memra

Memra

Remote
usememra.comMemory & Knowledge0Updated 7w ago

About Memra

Memra is a remote MCP server that gives AI agents persistent memory, with hybrid semantic and lexical recall and revision-aware updates. It is intended for agents that need to retain, search, and manage memories across sessions.

Key features

  1. 01Store and recall memories
  2. 02Hybrid semantic and lexical search
  3. 03Detect conflicting facts on write
  4. 04Track revisions and memory history
  5. 05Recall within a token budget
  6. 06Namespaces and scoped keys

Use cases

  1. 01Preserve facts and decisions across sessions
  2. 02Find memories by meaning or exact identifiers
  3. 03Identify and supersede outdated information
  4. 04Load priority context at session start

MCP support

Provides memory tools to MCP clients over Streamable HTTP, including remember, recall, supersede, history, and bootstrap operations. The README also describes a local alternative with the same tools.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://usememra.com/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

7
ParameterTypeRequiredDescription
maskbooleanNo
tagsarrayNo
typeenumNoMemory type; use decision for decision mode and pattern for pattern mode.fact | event | pattern | working | decision | preference | context | entity | reference
stepsarrayNoPattern mode: ordered steps. Required with title when type=pattern.
titlestringNoPattern mode: title. Required with steps when type=pattern.
contentstringNoSingle/decision mode: memory content. Required unless using entries[] or pattern mode.
contextstringNoDecision mode: reasoning/context for the decision.
entriesarrayNoBulk mode: array of memory entries (max 25). When provided, the server routes to batch create.
gotchasarrayNoPattern mode: common pitfalls.
metadataobjectNo
namespacestringNoTenant namespace. Required for single, decision, and pattern modes.
importanceintegerNo
project_idstringNoProject ID (required if account has multiple projects)
verify_checklistarrayNoPattern mode: verification checklist.

Details

From the project README

Memra MCP Server

Persistent memory for AI agents — remote MCP server. EU-hosted (Helsinki), privacy-first, deterministic recall with no LLM in the hot path.

Endpoint: https://usememra.com/mcp (Streamable HTTP) · Registry: com.usememra/memra · Free tier, no credit card.

What it gives your agent

  • memra_remember / memra_recall — store facts, decisions, patterns; hybrid semantic + lexical (BM25) search that also matches exact identifiers and error codes
  • Write-time contradiction detection — storing a fact that clashes with existing knowledge returns conflicts[] so the agent can supersede the outdated one
  • Read-your-writes — every write returns a revision token; recall with wait_for_revision is deterministic
  • memra_supersede + memra_history — memories retire with full audit chains instead of going stale
  • Staleness signals — every result carries staleness_score / last_confirmed; the agent decides what to trust
  • Token-budget recall — max_tokens: 2000 returns the best memories that fit your context window
  • memra_bootstrap — priority context at session start
  • Multi-tenant namespaces, PII masking (7 EU language models), read-only scoped keys for subagents

Setup

Get an API key at usememra.com (free tier), then:

Claude Code

claude mcp add --transport http memra https://usememra.com/mcp --header "Authorization: Bearer memra_live_YOUR_KEY"

Cursor / Cline / any MCP client (mcp.json)

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

Fully offline alternative: pip install memra-local — same tools, SQLite + ONNX embeddings, zero cloud calls.

Docs

SDKs: pip install memra-sdk · npm install @usememra/sdk · composer require memra/sdk

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.