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Memory and knowledge · MCP server

Memanto: MCP server, setup and security

Memanto is an open-source MCP server published on GitHub that lets an AI agent search and manage text or vector memory with RAG. Its repository has 2,340 stars and its last commit is from October 24, 2026 and it is licensed under MIT.

Actively maintainedTop 10% by stars

What Memanto does

According to its repository: “Universal memory agent for AI: provides semantic search, namespace management, text/vector operations and RAG for local or remote environments.”

The Model Context Protocol (MCP) is a standard plug between an AI agent and an outside service: once the server is connected, its tools show up in the agent, which decides when to call them. Memanto is listed under Memory and knowledge, a category of 250 servers in the directory, where it ranks #8 by stars.

Topics declared by the repository: ai-agents, memory, moorcheh, memanto, agent-memory, long-term-memory.

Installing and connecting Memanto

Distribution modes declared in the official MCP registry:

  • PyPI package (Python, started with uvx or pip)

It works with any MCP-compatible client (Claude Desktop, Claude Code, Cursor, VS Code, Codex and most recent agents). You add one entry to the client's MCP configuration: server name, start command or URL, environment variables. Project language: Python. Listed systems: macOS, Windows, Linux.

Security: what to check

Connecting an MCP server means installing software that talks straight to your agent: it runs with your rights and the model trusts its tool descriptions. The risk therefore depends on what it can touch and how far its code can be trusted.

None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to Memanto. That does not replace reading the code.

Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.

Project activity and maintenance

Created on March 23, 2026, the moorcheh-ai/memanto repository has 2,340 stars and 737 forks, with 5 open issues. It has more stars than 95% of the servers in the directory. It received changes this month. Version published in the registry: 0.1.4 (October 23, 2026).

Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.

Context7Context7 : 63.6K63.6KHindsightHindsight : 53.4K53.4KCogneeCognee : 32.7K32.7KSkill SeekersSkill Seekers : 15.2K15.2KHonchoHoncho : 7.8K7.8KBasic memoryBasic memory : 4.3K4.3KNoteDiscoveryNoteDiscovery : 2.8K2.8KMemantoMemanto : 2.3K2.3K
GitHub stars of the most followed servers in the category (log scale); Memanto in orange. Checked October 25, 2026.

Verdict

Memanto is one of the most solid servers in its category: followed, maintained and well framed.

Strengths

  • Active project: recent commit
  • Widely followed: 2.3K stars
  • Listed in the official MCP registry
  • Permissive licence (MIT)

Frequently asked questions

How do I install Memanto?

Memanto is distributed as PyPI package (Python, started with uvx or pip). Add it to your client's MCP configuration (Claude Desktop, Cursor, VS Code…) following the README of moorcheh-ai/memanto.

Is Memanto free?

The code is published under the MIT licence and can be used free of charge.

Is Memanto safe?

No risk signal found (system access, secrets, licence, abandonment). As with any MCP server, keep rights minimal and read the code before sensitive use.

Is it an official server?

Nothing says so: it is a project published by moorcheh-ai on GitHub. Check who maintains it before giving it access.

What are the alternatives to Memanto?

In the same category: Context7, Basic memory, Hindsight, and Cognee.

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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score