What is the key difference between Kage and Krimto?

Kage belongs to the Knowledge & Memory category with local stdio execution, while Krimto belongs to the Knowledge & Memory category with local stdio execution.

How do I install Kage or Krimto 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 Krimto free or paid?

Kage operates under a Free / Open Source model (No auth required). Krimto 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 32 GitHub stars. Krimto lists 6 tools with 2 views and 6 GitHub stars.

Can I use both Kage and Krimto 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 Kage or Krimto 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 Kage and Krimto free to use, or do they require API keys?

Kage is listed under a Free / Open Source model with No auth required . Krimto 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 Kage and Krimto at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both kage-core-kage and krimto-labs-krimto 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, Kage has a Quality Score of 61 /100 ( Good ) with 3 views, 0 installs, and 32 GitHub stars. Krimto holds a Quality Score of 53 /100 ( Good ) with 2 views, 0 installs, and 6 GitHub stars.

Side-by-Side Model Context Protocol Comparison

Kage vs Krimto

In-depth architectural comparison of the Kage and Krimto 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: 61/100 (Good) | Auth: No auth required

Krimto

Knowledge & Memory · Local stdio

Quality: 53/100 (Good) | Auth: No auth required

Verdict Summary: Choose Kage if you need specialized Knowledge & Memory tools running via a local process. Choose Krimto 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: Git-native memory packets, Open Knowledge Format bundles, Deterministic citation verification.

Explore Kage Details

Choose Krimto 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: Memory stored as plain markdown files in git, User→team→org scoped access control, Hybrid SQLite + vector index for fast retrieval.

Explore Krimto Details

Feature & Specification Comparison

Specification	Kage kage-core Knowledge & Memory	Krimto krimto-labs 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	Open-source team memory layer for AI coding agents. Markdown files in git as storage, a user→team→org hierarchy as the access primitive, and one cross-vendor MCP server (Claude Code, Cursor, Codex, Gemini CLI). Hybrid SQLite + sqlite-vec retrieval. Apache-2.0.
Category & Scope

Tools & Capabilities Breakdown

Kage Tools (6)

Git-native memory packets

Open Knowledge Format bundles

Deterministic citation verification

Stale-memory detection and withholding

Local BM25 and vector search

Agent wiring and MCP configuration

Krimto Tools (6)

Memory stored as plain markdown files in git

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",
        "install"
      ]
    }
  }
}

Krimto Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "krimto-labs-krimto": {
      "command": "npx",
      "args": [
        "-y",
        "@krimto-labs/krimto"
      ]
    }
  }
}

Frequently Asked Questions

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

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