head to head · open source
deep-searcher vs mcp-memory-service
deep-searcher has 8,381 GitHub stars, 816 forks, 55 open issues and last shipped 1 months ago. mcp-memory-service has 2,081 stars, 389 forks, 30 open issues and last shipped yesterday. deep-searcher leads on adoption by 303% (8,381 vs 2,081 stars). deep-searcher is written in Python under Apache-2.0; mcp-memory-service is written in Python under Apache-2.0. deep-searcher has attracted 10% as many forks as stars, mcp-memory-service 19%. mcp-memory-service was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (claude), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
← all 20902 open source comparisons
Side by side
| deep-searcher | mcp-memory-service | |
|---|---|---|
| GitHub stars | ★ 8.4K | ★ 2.1K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-09-22 | 2026-11-04 |
| Forks | ⑂ 816 | ⑂ 389 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick deep-searcher if
- You weight community size — 8.4K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick mcp-memory-service if
- You want the mcp-memory-service feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Python
- You evaluated both and mcp-memory-service fits your workflow better
About deep-searcher
DeepSearcher combines cutting edge LLMs (OpenAI o3, Qwen3, DeepSeek, Grok 4, Claude 4 Sonnet, Llama 4, QwQ, etc.) and Vector Databases (Milvus, Zilliz Cloud etc.) to perform search, evaluation, and reasoning based on private data, providing highly accurate answer and comprehensive report. This project is suitable for enterprise knowledge management, intelligent Q&A systems, and information retrieval scenarios. 🚀 Features Private Data Search : Maximizes the utilization of enterprise internal data while ensuring data security. When necessary, it can integrate online content for more accurate answers. Vector…
read the full deep-searcher overview →
About mcp-memory-service
This repository has moved to GitHub Active development, issues, pull requests, CI and releases are at as of 5 September 2026. This copy stays here, readable and unchanged, so that existing links, issue numbers and pull request references keep resolving. It receives no further pushes and its CI no longer runs. Please do not open issues or pull requests here, they will not be seen. The wiki moved too: mcp memory service Persistent Shared Memory for AI Agent Pipelines Open source memory backend for AI agents — REST API, MCP, OAuth, CLI, dashboard . One self hosted service, every transport. Agents store decisions…
read the full mcp-memory-service overview →
More in AI & Machine Learning
Related comparisons
More Machine Learning Infrastructure projects
Compare either of these against the rest of the Machine Learning Infrastructure field.
Frequently asked questions
Is deep-searcher or mcp-memory-service more popular?
deep-searcher has 8,381 GitHub stars and mcp-memory-service has 2,081. deep-searcher has the larger community by that measure.
Are deep-searcher and mcp-memory-service free?
Both are open source. deep-searcher is licensed under Apache-2.0 and mcp-memory-service under Apache-2.0. Neither carries a licence fee.
What is the difference between deep-searcher and mcp-memory-service?
deep-searcher is written in Python and mcp-memory-service in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, deep-searcher or mcp-memory-service?
Choose deep-searcher if you want the larger community (8,381 stars) or its Apache-2.0 licence terms. Choose mcp-memory-service if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.