identity-storage-mcp

identity-storage-mcp

Provides persistent, inspectable memory storage for AI agents using SQLite. Agents can store, recall, and search memories across sessions via three MCP tools.

Category
Visit Server

README

identity-storage

Portable, auditable long-term memory for AI agents. Runs as a local MCP server backed by a single SQLite file. Agents store and recall memories through three abstract tools; you audit the database with plain SQL.

Why

Agents like Claude Code, Codex, and opencode are stateless between sessions. identity-storage gives them a memory that survives restarts, works across clients, and stays fully inspectable — no ORM, no migration framework, no hidden state. Point sqlite3 at the file and read everything.

Install

pip install identity-storage

Or run it directly without installing:

uvx identity-storage-mcp

Configure your client

Claude Code

~/.config/claude/claude_desktop_config.json:

{
  "mcpServers": {
    "identity-storage": {
      "command": "uvx",
      "args": ["identity-storage-mcp"]
    }
  }
}

opencode

opencode.json:

{
  "mcp": {
    "identity-storage": {
      "type": "local",
      "command": ["uvx", "identity-storage-mcp"]
    }
  }
}

Codex / other MCP clients

Point the client at identity-storage-mcp over stdio. The server advertises three tools via tools/list; any MCP-compatible client picks them up.

Tools

The agent sees three tools, each scoped by memory_type (episodic, semantic, procedural, personality, emotional):

Tool Purpose
memory_store Persist a memory for future sessions
memory_recall Browse by type, tags, and time window (newest first)
memory_search Full-text search via SQLite FTS5 (ranked by relevance)

See docs/usage.md for the full input/output schemas.

Configuration

Env var Default Purpose
IDENTITY_STORAGE_DB ~/.identity-storage/memory.db SQLite database file path

The parent directory is created on first run. The schema is applied idempotently on every start, so pointing at a fresh path is safe.

Audit

The database is a regular SQLite file. Read it while the server runs (WAL mode allows concurrent reads):

sqlite3 ~/.identity-storage/memory.db
SELECT id, created_at, content FROM memory
WHERE type='episodic'
ORDER BY created_at DESC;

SELECT * FROM memory
WHERE EXISTS (SELECT 1 FROM json_each(tags) WHERE value='auth');

SELECT m.*
FROM memory m
JOIN memory_fts f ON f.rowid = m.rowid
WHERE f.content MATCH 'auth bug'
ORDER BY rank;

The schema lives in schemas/schema.sql and is the single source of truth. Run .schema in the sqlite3 CLI to see exactly what is in the file.

Documentation

Status

Alpha. The MCP contract and the SQLite schema are stable for the episodic case. Semantic memory, procedural memory, consolidation, and embeddings are planned — see docs/architecture.md for the roadmap shape.

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured