head to head · open source
txtai vs mcp-memory-service
txtai has 13,062 GitHub stars, 962 forks, 9 open issues and last shipped 2 days ago. mcp-memory-service has 2,073 stars, 386 forks, 30 open issues and last shipped yesterday. txtai leads on adoption by 530% (13,062 vs 2,073 stars). txtai is written in Python under Apache-2.0; mcp-memory-service is written in Python under Apache-2.0. txtai has attracted 7% 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 (ai-agents), 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
| txtai | mcp-memory-service | |
|---|---|---|
| GitHub stars | ★ 13K | ★ 2.1K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-03 | 2026-11-04 |
| Forks | ⑂ 962 | ⑂ 386 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick txtai if
- You weight community size — 13K 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 txtai
All in one AI framework txtai is an all in one AI framework for semantic search, LLM orchestration and language model workflows. The key component of txtai is an embeddings database, which is a union of vector indexes (sparse and dense), graph networks and relational databases. This foundation enables vector search and/or serves as a powerful knowledge source for large language model (LLM) applications. Build autonomous agents, retrieval augmented generation (RAG) processes, multi model workflows and more. Summary of txtai features: 🔎 Vector search with SQL, object storage, topic modeling, graph analysis and…
read the full txtai 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 txtai or mcp-memory-service more popular?
txtai has 13,062 GitHub stars and mcp-memory-service has 2,073. txtai has the larger community by that measure.
Are txtai and mcp-memory-service free?
Both are open source. txtai is licensed under Apache-2.0 and mcp-memory-service under Apache-2.0. Neither carries a licence fee.
What is the difference between txtai and mcp-memory-service?
txtai 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, txtai or mcp-memory-service?
Choose txtai if you want the larger community (13,062 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.