MCP.Market

Agentos MCP server

by OfficialTanishSharma·io.github.OfficialTanishSharma/agentos·v0.1.1·1 stars

Local-first persistent memory MCP server for AI coding agents.

B70/100grade B
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Safety scan
B70/100

full report

Adoption
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1 stars

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If you have run it, two minutes of your experience saves the next person an afternoon.

Agentos tools

No tool declarations could be read from the package source. They show once the server is installed.

Public scan report

scanner v0.1.10 · 2026-10-02 · same rubric, same numbers if you re-run it

no findings
  • –Code scanremote-only server, no package to scann/a
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualityno auth information5/15
  • Maintenancelast push 14 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 70/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Agentos compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
70/100
higher than 35% of 48,255 servers
GitHub stars
1
more than 65% of 28,688 servers

Release history: 2 versions in the registry since 2026-09-18, latest 2026-09-19, typically one every 1 day.

Install Agentos in Claude Code, Cursor or VS Code

The registry entry has no remote endpoint or installable package.

What the publisher says

From the Agentos repository's README, as published. We do not edit it. Read it on GitHub

AgentOS — Local-first persistent memory for AI coding agents

Phase 0.5 MVP: a small Rust MCP server that gives Claude Code persistent, project-scoped memory using SQLite FTS5.

Why AgentOS?

AI coding agents lose important context when a session ends. Architecture decisions, failed approaches, project conventions, and bug-fix details often have to be explained again.

AgentOS provides a small local memory layer that coding agents can access through MCP. Memories are stored in SQLite and retrieved with FTS5 keyword search—without a cloud account, embedding API, or external database.

Phase 0.5 is intentionally narrow: save explicit project memories and retrieve them in future Claude Code sessions.

Features

  • Persistent memory across Claude Code sessions
  • Local SQLite storage with bundled SQLite
  • Fast keyword retrieval through SQLite FTS5
  • Two focused MCP tools: memory.remember and memory.search
  • Project isolation using the MCP server's working directory
  • MCP JSON-RPC communication over standard input and output
  • No telemetry, network service, cloud database, or API key

Architecture

┌─────────────────────┐
│     Claude Code     │
└──────────┬──────────┘
           │
           │ MCP JSON-RPC
           │ newline-delimited stdio
           ▼
┌─────────────────────┐
│       AgentOS       │
│                     │
│  memory.remember    │
│  memory.search      │
└──────────┬──────────┘
           │
           │ rusqlite
           ▼
┌─────────────────────┐
│   SQLite + FTS5     │
│                     │
│  Local persistence  │
│  Keyword search     │
└─────────────────────┘

SQLite is the source of truth. The FTS5 index is kept synchronized with the memories table through SQLite triggers.

Quick Start

Requirements

AgentOS currently uses a Windows-first development workflow.

Install:

  • Windows 10 or Windows 11
  • Rust 1.80 or newer
  • Visual Studio 2022 Build Tools
  • The Desktop development with C++ workload
  • MSVC v143 build tools
  • Windows 10 or Windows 11 SDK
  • Claude Code

A separate SQLite installation is not required. AgentOS compiles and links bundled SQLite through rusqlite.

1. Clone the repository

Open PowerShell:

git clone https://github.com/OfficialTanishSharma/agentos.git
Set-Location .\agentos

2. Verify the Rust toolchain

rustc --version
cargo --version
rustup show

The active host should normally be:

x86_64-pc-windows-msvc

If required, select it explicitly:

rustup default stable-x86_64-pc-windows-msvc

3. Test and build AgentOS

cargo test
cargo build --release

The release binary will be created at:

target\release\agentos.exe

Verify it:

Get-Item .\target\release\agentos.exe

4. Connect AgentOS to Claude Code

Resolve the release binary to an absolute path:

$agentos = (Resolve-Path .\target\release\agentos.exe).Path

Register it as a project-scoped stdio MCP server:

claude mcp add --transport stdio --scope project agentos -- $agentos

Inspect the configuration and connection status:

claude mcp get agentos
claude mcp list

The expected status is:

✔ Connected

If the server is waiting for project approval, start Claude Code and approve the MCP configuration:

claude

5. Save a memory

Inside Claude Code, ask:

Call memory.remember with these values:

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Agentos: common questions

Is Agentos MCP server safe?
Mostly: it is graded B (70/100). Read the Agentos safety report
Does Agentos need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is Agentos maintained?
The last commit was 47 days ago (2026-09-18). The latest release is v0.1.1.
What can I use instead of Agentos?
Servers from other publishers that do the same job: Deja Vu MCP server, Memorix MCP server and Nautilus Compass Memory MCP server.
How does Agentos compare with other MCP servers?
safety score 70/100 (higher than 35% of 48,255 servers); github stars 1 (more than 65% of 28,688 servers). Full comparison.

Alternatives to Agentos

Same job from other publishers: the closest match first, then the best rated.

  • Deja Vu
    deja-vu: local memory over the session histories of forty-three coding agents.
    A
  • Memorix
    Local-first project memory with legacy MCP and 2026 discovery compatibility.
    B
  • Nautilus Compass Memory
    Local-first long-term memory for AI agents, with byte-recomputable signed verification receipts.
    B
  • State Memory MCP
    Persistent workflow graph server tracking tasks, decisions, spatial entities, and blockers.
    A
  • Knowl
    Persistent memory for AI agents, for code, research and everyday life. Stale facts retire.
    A