project-memory-mcp
Click on "Deploy 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., "@project-memory-mcp Remember: we decided to use SQLite for storage because it needs no extra services."
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.
project-memory-mcp
Coding agents forget everything between sessions. You explain a decision on Monday, and on Wednesday the agent re-derives it, differently. This is a small MCP server that gives agents a place to write things down and find them again — per project, across sessions, across tools.
It does three things and nothing else:
memory_record— save a note, decision, requirement, or learning.memory_search— full-text search over what was saved for a project.project_status— see whether a project has any memory yet, counts by kind, and the last few entries.
Everything lives in one SQLite file on your machine. No cloud, no accounts, no native dependencies — it uses the node:sqlite module that ships with Node, so pnpm install pulls in only the MCP SDK and zod.
How it works
Each tool call takes an absolute project_root. That path is the project's identity: the first time a memory is recorded for a root, a project row is created; after that every search and status call is scoped to it. Two projects can contain the same words and never see each other's memories.
Memory is append-only. Recording the same kind, title, and body twice stores it once and tells you created: false. There is no update or delete — to change a decision, record a new one with supersedes pointing at the old id; the old memory keeps its history but drops out of search results. That keeps the history honest and the tool surface tiny.
Search is deliberately boring: every word in your query must appear in a hit (title, body, or tags), ranked by SQLite's FTS5 with titles weighted highest, and the last word is a prefix match so sqlite finds sqlite3. Hits come back with a short excerpt, not the full body — pass include_body: true when you need the whole text. No query syntax to learn, no way to break it with punctuation.
Related MCP server: LumenCore
Getting started
Requires Node 26 and pnpm.
pnpm install
pnpm test
pnpm buildThen point your agent harness at the built server. For Claude Code, Codex, or anything else that reads an MCP config:
{
"mcpServers": {
"project-memory": {
"command": "node",
"args": ["/absolute/path/to/project-memory-mcp/dist/server.js"]
}
}
}The database is created on first use at ~/.local/share/project-memory/store.sqlite (or under $XDG_DATA_HOME if set). To put it somewhere else, set PROJECT_MEMORY_DB=/path/to/file.sqlite in the server's environment.
Teaching the agent to use it
Exposing tools is not the same as an agent knowing when to use them. skills/project-memory/SKILL.md is a short, harness-agnostic skill that tells the agent to resolve the project root once, check project_status before starting, search before re-deriving old decisions, and record requirements and decisions as they happen. Copy that folder into your harness's skills directory (for example ~/.claude/skills/ or ~/.codex/skills/) and adjust the server path in its setup section.
Kinds of memory
kind | use it for |
| a constraint the work must satisfy |
| a choice that was made, and why |
| a non-obvious fact about the code or environment |
| anything else worth keeping |
Project layout
src/server.ts stdio entry point
src/mcp.ts the three tool definitions
src/store.ts record / search / status against SQLite
src/db.ts schema, pragmas, database location
src/project-root.ts validates and canonicalizes project_root
test/ vitest: store behavior and MCP round-trips
skills/project-memory/SKILL.mdLicense
MIT
Available Tools
3 toolsmemory_recordRecord memoryAIdempotent
Record a durable memory (note, decision, requirement, or learning) for a project. Identical kind+title+body is stored once; the response reports created=false when it already existed. Pass supersedes= to mark an earlier memory as replaced by this one; superseded memories are hidden from search by default.
Inputs: body (required), kind (required), title (required), project_root (required), +2 more.
memory_searchSearch memoryARead-onlyIdempotent
Full-text search over a project's memories. Query words are matched literally (all words must appear) and the last word is a prefix match, so sqlite also finds sqlite3. Each hit carries a short excerpt over the body, not the full text. Returns newest-first among equal relevance. Empty results for unknown projects.
Inputs: query (required), project_root (required), kinds, limit, +2 more.
project_statusProject statusARead-onlyIdempotent
Report whether a project has recorded memory, counts by kind, and the 5 latest entries. Read-only.
Inputs: project_root (required).
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: recording, searching, and summarizing project memory. There is no overlap or ambiguity between them.
Names follow a predictable resource-prefixed pattern: memory_record, memory_search, project_status. The pattern is readable and consistent enough, though project_status is more of a noun phrase than an action-oriented name.
Three tools is well-scoped for a focused project-memory server. Each tool earns its place and the surface is small but not underwhelming.
Core memory workflows are covered: recording, searching, and checking status. A minor gap is the lack of a get-by-id or full-text retrieval tool, since search only returns excerpts; deletion is handled indirectly via supersede.
Related MCP Connectors
Project memory, documentation and controlled secret access for AI coding agents.
Project memory for coding agents: requirements, decisions, code graph and delivery telemetry.
Shared memory for coding agents. Stop re-explaining your codebase every session.
A notebook your coding agents write to: notes that track the code's commit, and handoffs.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to track, search, and retrieve their progress across projects with persistent memory using SQLite storage and LLM-powered summarization. Supports logging completed work, searching previous entries, and retrieving context for multi-step or multi-agent workflows.7 npmMIT
- AlicenseNot gradedqualityDmaintenanceProvides AI coding assistants with persistent project memory to retain architectural decisions, code patterns, and domain knowledge across sessions. It stores data locally in a SQLite database, allowing agents to remember, recall, and manage project-specific context using full-text search.4 npmApache 2.0
- AlicenseAqualityDmaintenanceProvides persistent cross-session memory and full-text search for AI coding assistants, storing project context, decisions, and preferences while enabling searchable access to conversation history via local SQLite.81MIT
- AlicenseAqualityBmaintenanceProvides AI coding assistants with persistent memory storage using a local SQLite database. Enables tools to remember project details, notes, and relationships across sessions to maintain context and reduce repetitive explanations.174MIT