init_projectLABSCO SUMMARY
Default-summary reading is the decision that makes memory affordable.
The failure mode of agent memory is that recalling it costs more context than it saves. Returning a table of section names, sizes and staleness — and no content — turns the read into a decision rather than a dump, and the agent then asks for the two sections it actually needs. The staleness and size warnings work the same way: they surface the sections that have quietly rotted, which is the thing nobody notices until the memory is actively wrong.
What it is
A persistent memory layer for AI coding agents, stored as local markdown files and shared across any IDE that speaks MCP. Project context is written once and read back everywhere. Projects are recognised by path or by git remote URL, so moving a folder or switching machines does not lose the memory.
What you get
- A project registered or reconnected, returning a memory summary with warnings — empty sections, sections stale beyond 7 days, sections over 10k chars, and content older than 30 days that suggests pruning —
init_project - Memory read in the mode you need: a compact summary table by default with no content at all, only named sections, a character cap per section, a keyword search across sections, previous versions, or everything with cleanup instructions —
read_memory - Sections written or appended, with the previous content saved to history automatically; append mode adds timestamped entries without rewriting —
write_memory - Projects listed or deleted —
manage_projects - Three prompt templates that tell the agent when to use memory at all:
start_sessionat the beginning of a conversation,bootstrap_memoryfor learning an existing project,update_memoryat the end of a productive session - Default sections for every project —
overview,decisions,active_context,progress— plus any custom ones you add, with the last 5 snapshots kept per section
Requirements
No account, no database, no cloud — local markdown files. Python 3.11+; install with uv pip install ide-memory-mcp or pip, then run ide-memory-mcp setup to detect and configure installed IDEs (Cursor, VS Code, Windsurf, Claude Desktop) and restart the IDE. Manual configuration is a one-line command entry in the IDE's MCP config. Two helper commands come with it: doctor verifies the install, storage use and which IDEs are configured, and status lists projects with section counts, size and last update. The pyproject name is ide-memory-mcp (1.0.0), MIT licensed.
Setup effort
One command — pip install ide-memory-mcp
USE CASES
Starting a conversation without re-explaining the project
Initialise the project, read the summary table, and load only the sections relevant to today's work.
Teaching the assistant an existing codebase once
Run the bootstrap prompt so it reads the README and package files, then writes the overview, decisions and current state itself.
Carrying context between two editors
Write in Cursor, read in VS Code — the same project memory, matched by path or git remote.
Keeping the memory from going stale
Append decisions and progress as they happen, and act on the warnings when a section is old or oversized.
4 tools
Listed in project docs. Your client may show a different list.
read_memorywrite_memorymanage_projectsBEFORE YOU INSTALL
What to know first
Tools you get
4 tools named in the project's documentation.
Requires
- ide-memory-mcp on PATH
- Python 3.11+
Where it runs
All 4 documented clients run the server on your machine.
INSTALLATION
Connect your client
Server setup
pip install ide-memory-mcpMCP Clients
Cursor, Windsurf, Claude Desktop
{
"mcpServers": {
"ide-memory": {
"command": "ide-memory-mcp"
}
}
}VS Code
{
"servers": {
"ide-memory": {
"command": "ide-memory-mcp"
}
}
}