head to head · open source
llama.cpp vs mcp-memory-service
llama.cpp has 128,619 GitHub stars, 23,351 forks, 2,464 open issues and last shipped today. mcp-memory-service has 1,951 stars, 319 forks, 30 open issues and last shipped yesterday. llama.cpp leads on adoption by 6,492% (128,619 vs 1,951 stars). llama.cpp is written in C++ under MIT; mcp-memory-service is written in Python under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, mcp-memory-service 16%. llama.cpp was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| llama.cpp | mcp-memory-service | |
|---|---|---|
| GitHub stars | ★ 129K | ★ 2.0K |
| License | MIT | Apache-2.0 |
| Written in | C++ | Python |
| Last push | 2026-09-18 | 2026-09-17 |
| Forks | ⑂ 23K | ⑂ 319 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick llama.cpp if
- You weight community size — 129K stars and counting
- You want the MIT license terms
- Your stack matches C++
- 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 llama.cpp
llama.cpp is a C/C++ library and set of command line tools for running large language models (LLMs) and vision language models (VLMs) locally. It enables inference without external dependencies, targeting diverse hardware including Apple Silicon, x86 CPUs, NVIDIA GPUs (via CUDA), AMD GPUs (via HIP), and other accelerators. The project lives in the ggml ecosystem, leveraging the ggml tensor computation library for low level operations and quantized model execution.
read the full llama.cpp 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, sh…
read the full mcp-memory-service overview →
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Frequently asked questions
Is llama.cpp or mcp-memory-service more popular?
llama.cpp has 128,619 GitHub stars and mcp-memory-service has 1,951. llama.cpp has the larger community by that measure.
Are llama.cpp and mcp-memory-service free?
Both are open source. llama.cpp is licensed under MIT and mcp-memory-service under Apache-2.0. Neither carries a licence fee.
What is the difference between llama.cpp and mcp-memory-service?
llama.cpp is written in C++ 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, llama.cpp or mcp-memory-service?
Choose llama.cpp if you want the larger community (128,619 stars) or its MIT licence terms. Choose mcp-memory-service if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.