What is the key difference between Kage and Iranti?

Kage 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 Kage 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 Kage and Iranti free or paid?

Kage 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?

Kage lists 6 tools with 3 views and 33 GitHub stars. Iranti lists 6 tools with 1 views and 5 GitHub stars.

Can I use both Kage 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.

Side-by-Side Model Context Protocol Comparison

Kage vs Iranti

In-depth architectural comparison of the Kage 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

Kage

Knowledge & Memory · Local stdio

Quality: 60/100 (Good) | Auth: No auth required

Iranti

Knowledge & Memory · Local stdio

Quality: 44/100 (Fair) | Auth: No auth required

Verdict Summary: Choose Kage 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 Kage 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: OKF-compatible Markdown memory in Git, Citation validation at write and recall time, Local BM25 and vector retrieval.

Explore Kage 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: Persistent shared memory, Entity/key/value fact storage, Hybrid semantic search.

Explore Iranti Details

Feature & Specification Comparison

Specification	Kage kage-core Knowledge & Memory	Iranti nfemmanuel Knowledge & Memory
Summary	Verified, git-native memory for coding agents. Memory is plain JSON packets committed in your repo, each checked against the code it cites — hallucinated citations rejected at write, stale or changed memory withheld at recall, plus diff-time stale-catch. Local-only (BM25 + vectors), no account, no API key. npx -y @kage-core/kage-graph-mcp install	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

Tools & Capabilities Breakdown

Kage Tools (6)

OKF-compatible Markdown memory in Git

Citation validation at write and recall time

Local BM25 and vector retrieval

Isolated worktree orchestration

Independent test, diff, and citation checks

Agent setup and local project UI

Iranti Tools (6)

Persistent shared memory

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).

Kage Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "kage-core-kage": {
      "command": "npx",
      "args": [
        "-y",
        "@kage-core/kage-graph-mcp"
      ]
    }
  }
}

Iranti Configuration

mcpServers (Claude Desktop / Cursor)

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

Frequently Asked Questions

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

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