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
- 01Store and recall memories
- 02Hybrid semantic and lexical search
- 03Detect conflicting facts on write
- 04Track revisions and memory history
- 05Recall within a token budget
- 06Namespaces and scoped keys
Use cases
- 01Preserve facts and decisions across sessions
- 02Find memories by meaning or exact identifiers
- 03Identify and supersede outdated information
- 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.
https://usememra.com/mcpclaude mcp add --transport http usememra https://usememra.com/mcp{"mcpServers":{"usememra":{"type":"http","url":"https://usememra.com/mcp"}}}Open in Cursor{"servers":{"usememra":{"type":"http","url":"https://usememra.com/mcp"}}}Open in VS Code{"mcpServers":{"usememra":{"type":"http","url":"https://usememra.com/mcp"}}}{"mcpServers":{"usememra":{"serverUrl":"https://usememra.com/mcp"}}}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| Parameter | Type | Required | Description |
|---|---|---|---|
| mask | boolean | No | |
| tags | array | No | |
| type | enum | No | Memory type; use decision for decision mode and pattern for pattern mode.fact | event | pattern | working | decision | preference | context | entity | reference |
| steps | array | No | Pattern mode: ordered steps. Required with title when type=pattern. |
| title | string | No | Pattern mode: title. Required with steps when type=pattern. |
| content | string | No | Single/decision mode: memory content. Required unless using entries[] or pattern mode. |
| context | string | No | Decision mode: reasoning/context for the decision. |
| entries | array | No | Bulk mode: array of memory entries (max 25). When provided, the server routes to batch create. |
| gotchas | array | No | Pattern mode: common pitfalls. |
| metadata | object | No | |
| namespace | string | No | Tenant namespace. Required for single, decision, and pattern modes. |
| importance | integer | No | |
| project_id | string | No | Project ID (required if account has multiple projects) |
| verify_checklist | array | No | Pattern mode: verification checklist. |
Details
From the project READMEMemra 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
revisiontoken; recall withwait_for_revisionis 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: 2000returns 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
- llms-full.txt — complete machine-readable API reference
- OpenAPI · Changelog · Security · Data & privacy
SDKs: pip install memra-sdk · npm install @usememra/sdk · composer require memra/sdk
Comments
New to MCP?
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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.