Local LLM
codanna
Local code-intelligence MCP server and CLI for coding agents.
★ 744 starsApache-2.0
View guide →Local codebase intelligence CLI and MCP for coding agents.
roam-code is an open-source local llm project by Cranot (Cranot/roam-code on GitHub). It has 517 GitHub stars and 50 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 3 October 2026.
Get it from the official site.
Build the SQLite code graph.
Analyze code from the shell.
Expose it over MCP.
Structural index of your repo.
Broad language coverage.
Deep analysis and review tooling.
Agents query the graph.
Nothing leaves your machine.
Free for commercial use.
Download the source and enter the folder.
git clone https://github.com/Cranot/roam-code.git
cd roam-codeSet up the Python package.
pip install -e .Build the code graph.
roam-code index /path/to/repoA local codebase-intelligence CLI and MCP server for coding agents, at Cranot/roam-code.
28, per the project docs.
Over MCP, querying the SQLite code graph.
Yes. Apache-2.0 licensed.
Code analysis, review, and quality checks via its command set.
Local code-intelligence MCP server and CLI for coding agents.
An MCP server plus a CLI tool that indexes local code into a graph database to provide context to AI assistants.
Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors
Secure MCP runtime letting AI agents operate your local machines.
Open source, Git-native memory for AI coding agents - deterministic local recall
Local-first desktop where a commander LLM directs specialist coding agents.
The most-starred other Local LLM projects in the LibreAI catalogue — the realistic shortlist if roam-code is not the right fit.
The simplest way to run open language models on your own machine.
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
LLM inference in C/C++
A high-throughput and memory-efficient inference and serving engine for LLMs
🤯 LobeHub is your Chief Agent Operator, organizing your agents into 7×24 operations by hiring, scheduling, and reporting on your entire AI team.
Free and open — grab the source, star the repo, and start creating.