What is the key difference between A2cr and Iranti?

A2cr belongs to the Knowledge & Memory category with local stdio execution, while Iranti belongs to the Knowledge & Memory category with local stdio execution.

How do I install A2cr or Iranti in Claude Desktop or Cursor?

Copy the mcpServers JSON configuration snippet provided on this page into your claude_desktop_config.json or ~/.cursor/mcp.json file and restart your AI client.

Are A2cr and Iranti free or paid?

A2cr operates under a Free / Open Source model (No auth required). Iranti operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

A2cr lists 6 tools with 3 views and 2 GitHub stars. Iranti lists 5 tools with 0 views and 5 GitHub stars.

Can I use both A2cr and Iranti together in the same MCP host?

Yes! MCP hosts like Claude Desktop, Cursor, Windsurf, Cline, and VS Code support configuring multiple servers under the mcpServers object simultaneously.

How do I install A2cr or Iranti in Claude Desktop, Cursor, or Windsurf?

Both servers follow the standard Model Context Protocol configuration format. Simply copy the JSON block from the configuration section above and paste it into your AI client's mcpServers configuration object (for instance in claude_desktop_config.json or ~/.cursor/mcp.json ), then completely restart or refresh the application.

Are A2cr and Iranti free to use, or do they require API keys?

A2cr is listed under a Free / Open Source model with No auth required . Iranti operates under a Free / Open Source model with No auth required . If environment variables are required (such as API keys), be sure to define them under the env key in your MCP client's configuration file.

Can I run both A2cr and Iranti at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both a2cr-a2cr and nfemmanuel-iranti as distinct keys inside the single mcpServers object in your configuration file. Your AI assistant will automatically select and call the appropriate tool from either server during chat sessions.

Which MCP server has higher directory engagement and quality ratings?

On AllMCPs, A2cr has a Quality Score of 43 /100 ( Fair ) with 3 views, 0 installs, and 2 GitHub stars. Iranti holds a Quality Score of 40 /100 ( Fair ) with 0 views, 0 installs, and 5 GitHub stars.

Side-by-Side Model Context Protocol Comparison

A2cr vs Iranti

In-depth architectural comparison of the A2cr and Iranti MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.

At a Glance & Executive Verdict

A2cr

Knowledge & Memory · Local stdio

Quality: 43/100 (Fair) | Auth: No auth required

Iranti

Knowledge & Memory · Local stdio

Quality: 40/100 (Fair) | Auth: No auth required

Verdict Summary: Choose A2cr if you need specialized Knowledge & Memory tools running via a local process. Choose Iranti if your workspace requires Knowledge & Memory integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.

Which MCP Server Should You Choose?

Choose A2cr when:

You need dedicated capabilities in the Knowledge & Memory domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
You have access to required keys: A2CR_LOCAL_DB, A2CR_UI_URL.
Primary tools included: Stores WorkBaton, WorkStash, WorkThread, actor, and event records locally, Client-encrypted checkpoint and note storage, SQLite database backend with no cloud or account needed.

Explore A2cr Details

Choose Iranti when:

You need dedicated capabilities in the Knowledge & Memory domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Primary tools included: Entity/key/value triple storage, Hybrid semantic search capability, Task checkpoint management.

Feature & Specification Comparison

Specification	A2cr a2cr Knowledge & Memory	Iranti nfemmanuel Knowledge & Memory
Summary	MCP server for AI-agent handoffs. Saves client-encrypted WorkBaton checkpoints and WorkStash notes so Codex, Claude Code, Roo Code, and other MCP clients can resume work without passing full chat history.	Persistent shared memory for AI coding agents. Stores facts as entity/key/value triples with hybrid semantic search, task checkpoints, and conflict resolution — shared across Claude Code, Codex CLI, and GitHub Copilot.
Category & Scope	Knowledge & Memory

Tools & Capabilities Breakdown

A2cr Tools (6)

Stores WorkBaton, WorkStash, WorkThread, actor, and event records locally

Client-encrypted checkpoint and note storage

SQLite database backend with no cloud or account needed

Supports multiple MCP clients including Codex, Claude Code, and Cursor

Local browser dashboard with token-protected access

Compatibility with Python stdio wrapper and Node MCPB for Claude Desktop

Iranti Tools (5)

Ready-to-Paste Client Configurations

Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).

A2cr Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "a2cr-a2cr": {
      "command": "npx",
      "args": [
        "-y",
        "a2cr-a2cr"
      ],
      "env": {
        "A2CR_LOCAL_DB": "YOUR_A2CR_LOCAL_DB_HERE",
        "A2CR_UI_URL": "YOUR_A2CR_UI_URL_HERE"
      }
    }
  }
}

Iranti Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "nfemmanuel-iranti": {
      "command": "npx",
      "args": [
        "-y",
        "nfemmanuel-iranti"
      ]
    }
  }
}

Frequently Asked Questions

A2cr is categorized under Knowledge & Memory and uses a local stdio subprocess. In contrast, Iranti belongs to Knowledge & Memory using local stdio subprocess. Select A2cr when you need capabilities focused on knowledge & memory and Iranti when you require tools for knowledge & memory.

More alternatives to A2cr More alternatives to Iranti Knowledge & Memory category hub