MCPSaver
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCPSaversearch memory for pytest fixture usage"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCPSaver
Local MCP server for persistent, searchable agent memory.
Full landing page: cpntodd.github.io/MCPSaver
MCPSaver replaces flat MEMORY.md files with a SQLite database behind a Model Context Protocol (MCP) server. It provides full-text search (FTS5), workspace context caching, and code symbol indexing -- all running locally over stdio.
Why
Flat Markdown memory files force the agent to read the entire file to find one relevant lesson, burning thousands of tokens on irrelevant history. MCPSaver gives the agent queryable long-term memory with selective retrieval:
Operation | Flat MEMORY.md | MCPSaver |
Find a past lesson | Read entire file (~2000 tokens) |
|
Load project context | Run |
|
Record a new lesson | Append to |
|
Check prior art | Grep codebase (~300 tokens) |
|
Related MCP server: agent-memory
Install
git clone https://github.com/cpntodd/MCPSaver.git
cd MCPSaver
uv syncRequires Python >= 3.13.
VS Code Configuration
Add to your VS Code mcp.json (User or Workspace settings):
{
"servers": {
"mcpsaver": {
"type": "stdio",
"command": "uv",
"args": [
"--directory",
"/path/to/MCPSaver",
"run",
"mcpsaver"
]
}
}
}Or use the Claude Desktop / Cursor equivalent for your MCP client.
Tools
record_lesson
Store a lesson, convention, or correction into persistent memory.
record_lesson(
lesson_type: "convention" | "self_correction" | "human_correction" | "api_fact" | "decision" | "pattern",
context: string,
correction: string,
mistake?: string,
pattern?: string,
tags?: string[],
workspace?: string
)search_memory
Full-text search across all lessons using SQLite FTS5 with porter stemming.
search_memory(
query: string,
limit?: int (default 10),
tags?: string[]
)get_workspace_context / set_workspace_context
Cache and retrieve project metadata (stack, linter, formatter, file tree).
get_workspace_context(workspace: string)
set_workspace_context(
workspace: string,
stack?: string[],
linter?: string,
formatter?: string,
test_runner?: string,
file_tree?: string,
conventions?: object
)find_prior_art / index_symbols
Search indexed code symbols to find prior usage of functions, classes, or patterns.
find_prior_art(
workspace: string,
symbol?: string,
kind?: string,
limit?: int
)
index_symbols(
workspace: string,
symbols: [{symbol, kind?, file_path, line?, snippet?}],
clear_first?: bool
)list_lessons
List recent lessons with optional type/workspace filters.
get_stats
Return summary statistics about the memory database.
import_memory_md
Import existing MEMORY.md flat files into the SQLite database.
Architecture
~/.local/share/mcpsaver/memory.db <-- SQLite database (auto-created)
|
+-- lessons <-- Core lessons table (all memory entries)
+-- lessons_fts <-- FTS5 full-text index (porter stemming)
+-- workspace_context <-- Cached project metadata per workspace
+-- code_symbols <-- Indexed code symbols per workspaceStorage
All data lives in ~/.local/share/mcpsaver/memory.db. Nothing leaves the machine. The MCP server communicates exclusively over stdio with no network access.
License
GPL-3.0-or-later
(c) 2026 cpntodd
This server cannot be installed
Maintenance
Resources
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Looking for Admin?
If you are the server author, to access and configure the admin panel.
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