What is the key difference between Memora and Iranti?

Memora 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 Memora 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 Memora and Iranti free or paid?

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

Which MCP server has more tools and community activity?

Memora lists 6 tools with 2 views and 633 GitHub stars. Iranti lists 6 tools with 1 views and 5 GitHub stars.

Can I use both Memora 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 Memora 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 Memora and Iranti free to use, or do they require API keys?

Memora is listed under a BYOK (Pay Provider Direct) model with API Key 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 Memora and Iranti at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both agentic-mcp-tools-memora 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, Memora has a Quality Score of 63 /100 ( Good ) with 2 views, 0 installs, and 633 GitHub stars. Iranti holds a Quality Score of 44 /100 ( Fair ) with 1 views, 0 installs, and 5 GitHub stars.

Side-by-Side Model Context Protocol Comparison

Memora vs Iranti

In-depth architectural comparison of the Memora 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

Memora

Knowledge & Memory · Local stdio

Quality: 63/100 (Good) | Auth: API Key required

Iranti

Knowledge & Memory · Local stdio

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

Verdict Summary: Choose Memora 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 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.

Explore Memora 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).

Feature & Specification Comparison

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

Memora Tools (6)

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

Knowledge graph visualization with Mermaid and live graph server

Memory linking with typed edges and AI-powered deduplication

RAG-powered chat interface for memory querying and updates

Iranti Tools (6)

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).

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"
      }
    }
  }
}

Iranti Configuration

mcpServers (Claude Desktop / Cursor)

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

Frequently Asked Questions

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

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