What is the key difference between Iranti and Memora?

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

How do I install Iranti or Memora 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 Iranti and Memora free or paid?

Iranti operates under a Free / Open Source model (No auth required). Memora operates under a BYOK (Pay Provider Direct) model (API Key required).

Which MCP server has more tools and community activity?

Iranti lists 6 tools with 1 views and 5 GitHub stars. Memora lists 6 tools with 2 views and 719 GitHub stars.

Can I use both Iranti and Memora 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

Iranti vs Memora

In-depth architectural comparison of the Iranti and Memora 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

Iranti

Knowledge & Memory · Local stdio

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

Memora

Knowledge & Memory · Local stdio

Quality: 56/100 (Good) | Auth: API Key required

Verdict Summary: Choose Iranti if you need specialized Knowledge & Memory tools running via a local process. Choose Memora 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 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

Choose Memora when:

You need dedicated capabilities in the Knowledge & Memory domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: API Key required (BYOK (Pay Provider Direct)).
You have access to required keys: MEMORA_DB_PATH, MEMORA_STORAGE_URI, CLOUDFLARE_API_TOKEN, AWS_PROFILE, AWS_ENDPOINT_URL, MEMORA_CLOUD_ENCRYPT, MEMORA_ALLOW_ANY_TAG, MEMORA_GRAPH_PORT.
Primary tools included: Persistent storage with SQLite or cloud sync (S3, R2, D1), Hierarchical memory organization with sections and subsections, Semantic search using TF-IDF, sentence-transformers, and OpenAI embeddings.

Feature & Specification Comparison

Specification	Iranti nfemmanuel Knowledge & Memory	Memora agentic-mcp-tools Knowledge & Memory
Summary	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.	Persistent memory with knowledge graph visualization, semantic/hybrid search, cloud sync (S3/R2), and cross-session context management.
Category & Scope

Tools & Capabilities Breakdown

Iranti Tools (6)

Persistent shared memory

Entity/key/value fact storage

Hybrid semantic search

Task checkpoints

Conflict resolution

Support for Claude Code, Codex CLI, and GitHub Copilot

Memora Tools (6)

Persistent storage with SQLite or cloud sync (S3, R2, D1)

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).

Iranti Configuration

mcpServers (Claude Desktop / Cursor)

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

Memora Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "agentic-mcp-tools-memora": {
      "command": "npx",
      "args": [
        "-y",
        "wrangler"
      ],
      "env": {
        "MEMORA_DB_PATH": "YOUR_MEMORA_DB_PATH_HERE",
        "MEMORA_STORAGE_URI": "YOUR_MEMORA_STORAGE_URI_HERE",
        "CLOUDFLARE_API_TOKEN": "YOUR_CLOUDFLARE_API_TOKEN_HERE",
        "AWS_PROFILE": "YOUR_AWS_PROFILE_HERE",
        "AWS_ENDPOINT_URL": "YOUR_AWS_ENDPOINT_URL_HERE",
        "MEMORA_CLOUD_ENCRYPT": "YOUR_MEMORA_CLOUD_ENCRYPT_HERE",
        "MEMORA_ALLOW_ANY_TAG": "YOUR_MEMORA_ALLOW_ANY_TAG_HERE",
        "MEMORA_GRAPH_PORT": "YOUR_MEMORA_GRAPH_PORT_HERE"
      }
    }
  }
}

Frequently Asked Questions

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

More alternatives to Iranti More alternatives to Memora Knowledge & Memory category hub Canonical compare URL