Memory MCP vs Travel Planner MCP Agent
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. Travel Planner MCP Agent suits teams needing open-source access, flight search focus, and 133,530 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 | Travel Planner MCP Agent |
|---|---|---|
| GitHub Stars | 89.8K | 133.5K |
| Contributors | 426 | 95 |
| Last Commit | Aug 20, 2026 | Aug 22, 2026 |
| Open Issues | 533 | 14 |
| 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 has a larger visible contributor base (426 vs 95).
- • Memory MCP is the cleaner fit if you specifically need Memory workflows from the catalog tags.
Choose Travel Planner MCP Agent if you need
- • Travel Planner MCP Agent is the stronger pick when Flight Search matters because that capability is listed only on its profile.
- • Travel Planner MCP Agent shows broader GitHub adoption with 133,530 stars versus 89,768 for Memory MCP.
- • Travel Planner MCP Agent is the cleaner fit if you specifically need Mcp workflows from the catalog tags.
Meaningful differences
- • GitHub adoption: Memory MCP shows 89,768 stars versus 133,530 for Travel Planner MCP Agent.
- • Contributor count: Memory MCP lists 426 contributors and Travel Planner MCP Agent lists 95.
Shared capabilities
- • No shared capabilities are explicitly listed in the stored metadata.
Shared Tags
Only in Memory MCP
Only in Travel Planner MCP Agent
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 Travel Planner MCP Agent
An MCP server that gives AI assistants access to travel planning tools: flight search, hotel lookup, itinerary generation, and destination research. Demonstrates how to build custom MCP servers with multiple tools that chain together for complex multi-step workflows. Part of the awesome-llm-apps collection.
View full listing