LinkLore — project memory MCP server for Claude Code and Codex
Structured memory for AI agents: decisions, pitfalls and specs get recorded as the agent works, then surface next session with code context attached.
claude mcp add --env LINKLORE_LANG=<LINKLORE_LANG> --transport stdio linklore -- uvx llreWhat LinkLore does
A fresh agent session starts from zero. Decisions get argued again, pitfalls get hit twice, and the reason behind a weird implementation becomes a guess. LinkLore fixes this with MCP tools the agent reads and writes itself. Two record types — lore for decisions and pitfalls, doc for specs and plans — link to each other and to source files.
Everything lives in a .linklore/ SQLite store inside your project. No account needed. Records point at code files, and git-diff-based drift detection shows where memory has fallen behind the code. Search by meaning, tag, file, status or period. At session start, brief() compiles open items and hotspots into a compact summary.
The package runs from PyPI via uvx llre, no clone needed. For Claude Code: claude mcp add llre -- uvx llre, then uvx llre init once in the project root. Core modules — search, ranking, tool logic — ship as compiled extensions, so reading every line and forking is not fully possible. Most of the source is open, but the crown-jewel logic is closed. Elastic License 2.0: free to install and use commercially inside your org, but you cannot offer it as a competing managed service.
What it helps with
- Keep decisions and pitfalls from one session to the next
- Find out why code is written this way instead of guessing
- Tie specs to code files instead of separate markdown notes
- Catch memory that has drifted from the code via git-diff
- Clean up near-duplicate records and check store integrity
Example prompts for the agent
- Set up LinkLore in this repo: PyPI package
llre, run viauvx llre, register it as an MCP server, then runuvx llre init - At session start call
brief()and show open items and hotspots - Before editing this file, pull decisions tied to it with
show(file=..., query=...)
How to install LinkLore
Platform CLI
claude mcp add --env LINKLORE_LANG=<LINKLORE_LANG> --transport stdio linklore -- uvx llreReplace <…> with your own values. uvx runs the command named after the package; if the README names another one, use uvx --from llre <command>
Platform CLI
codex mcp add linklore --env LINKLORE_LANG=<LINKLORE_LANG> -- uvx llreReplace <…> with your own values. uvx runs the command named after the package; if the README names another one, use uvx --from llre <command>
Config file
{
"mcpServers": {
"linklore": {
"command": "uvx",
"args": [
"llre"
],
"env": {
"LINKLORE_LANG": "<LINKLORE_LANG>"
}
}
}
}Replace <…> with your own values. uvx runs the command named after the package; if the README names another one, use uvx --from llre <command>
Config file
{
"servers": {
"linklore": {
"type": "stdio",
"command": "uvx",
"args": [
"llre"
],
"env": {
"LINKLORE_LANG": "<LINKLORE_LANG>"
}
}
}
}Replace <…> with your own values. uvx runs the command named after the package; if the README names another one, use uvx --from llre <command>
Platform CLI
gemini mcp add -e LINKLORE_LANG=<LINKLORE_LANG> linklore uvx llreReplace <…> with your own values. uvx runs the command named after the package; if the README names another one, use uvx --from llre <command>
Step by step, with commands for each platform: How to add an MCP server to Claude Code, Codex, Cursor, VS Code, Gemini CLI and more
Questions about LinkLore
How do I install LinkLore in Claude Code?
Run claude mcp add llre -- uvx llre, then uvx llre init once in the project root. With a language variable: claude mcp add --env LINKLORE_LANG=<LINKLORE_LANG> --transport stdio linklore -- uvx llre.
What does LinkLore do?
It gives the agent a structured project memory. Lore and doc records link to code files, and a session-start brief() returns open items and hotspots as a short summary.
Do I need an account?
No. Everything stays local in .linklore/ inside the project. Google login via uvx llre login is only for personal backup or team sharing.
