Memory MCP vs n8n MCP Server
Side-by-side comparison built from DeepYard's structured catalog. Content updated Aug 21, 2026.
Direct Answer
Memory MCP suits teams needing open-source access, persistent memory focus, and 89,768 GitHub stars in current listing data. n8n MCP Server suits teams needing open-source access, workflow creation focus, and 22,752 GitHub stars in current listing data. This summary reflects catalog metadata only for decision support, not independent testing.
What this comparison weighs
- Pricing and free-tier availability
- License model and deployment fit
- GitHub adoption and contributor depth
- Catalog tags, integrations, and supported workflows
| Metric | Memory MCP | n8n MCP Server |
|---|---|---|
| GitHub Stars | 89.8K | 22.8K |
| Contributors | 426 | 30 |
| Last Commit | Aug 20, 2026 | Aug 19, 2026 |
| Open Issues | 533 | 59 |
| License | open-source | open-source |
| Pricing | open-source | open-source |
| Free Tier | Yes | Yes |
| Category | mcp-servers | mcp-servers |
| Trending | No | No |
Choose Memory MCP if you need
- • Memory MCP is the stronger pick when Persistent Memory matters because that capability is listed only on its profile.
- • Memory MCP shows broader GitHub adoption with 89,768 stars versus 22,752 for n8n MCP Server.
- • Memory MCP has a larger visible contributor base (426 vs 30).
Choose n8n MCP Server if you need
- • n8n MCP Server is the stronger pick when Workflow Creation matters because that capability is listed only on its profile.
- • n8n MCP Server is the cleaner fit if you specifically need N8n workflows from the catalog tags.
Meaningful differences
- • GitHub adoption: Memory MCP shows 89,768 stars versus 22,752 for n8n MCP Server.
- • Contributor count: Memory MCP lists 426 contributors and n8n MCP Server lists 30.
Shared capabilities
- • No shared capabilities are explicitly listed in the stored metadata.
Shared Tags
Only in Memory MCP
Only in n8n MCP Server
Limitations and evidence
- • DeepYard compares structured public metadata; this is not an independent benchmark unless a test record is shown.
- • Signals such as stars, contributors, and last commit indicate public activity, not purchase fit or runtime quality.
- • Pricing and feature coverage reflect the stored listing snapshot and may lag vendor changes between refreshes.
Source links
About Memory MCP
The official Anthropic memory MCP server gives AI assistants persistent, cross-session memory using a local knowledge graph stored as a JSON file. Claude can create entities (people, projects, concepts), record relations between them, and add observations over time — then recall that information in future sessions. Ideal for long-running projects where continuity matters: the assistant remembers your architecture decisions, team conventions, and in-progress work without you having to repeat context.
View full listingAbout n8n MCP Server
An MCP server that lets AI coding agents create, edit, and manage n8n workflows. Connect Claude Desktop, Cursor, or Claude Code to your n8n instance and build automations through natural language. Agents can create workflows, add nodes, configure connections, and activate automations without touching the n8n UI.
View full listing