What is the key difference between Bay Run and Memora?

Bay Run 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 Bay Run 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 Bay Run and Memora free or paid?

Bay Run 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?

Bay Run lists 0 tools with 0 views and 0 GitHub stars. Memora lists 6 tools with 2 views and 719 GitHub stars.

Can I use both Bay Run 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

Bay Run vs Memora

In-depth architectural comparison of the Bay Run 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

Bay Run

Knowledge & Memory · Local stdio

Quality: 29/100 (Emerging) | Auth: No auth required

Memora

Knowledge & Memory · Local stdio

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

Verdict Summary: Choose Bay Run 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 Bay Run 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).

Explore Bay Run 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	Bay Run Knowledge & Memory	Memora agentic-mcp-tools Knowledge & Memory
Summary	Discover, prove, and serve small open specialist models (embeddings, rerank) — OpenAI-compatible.	Persistent memory with knowledge graph visualization, semantic/hybrid search, cloud sync (S3/R2), and cross-session context management.
Category & Scope	Knowledge & Memory

Tools & Capabilities Breakdown

Bay Run Tools (0)

No explicit tool names declared in metadata yet. Check project README on main listing page.

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

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).

Bay Run Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "bay-run": {
      "command": "npx",
      "args": [
        "-y",
        "bay-run"
      ]
    }
  }
}

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

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

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