Datacore gives them a structured, plain-text second brain — capture journal entries and knowledge notes, search them back, get canonical date handling, and extend with modules (GTD, health, trading, and more).

Persistent memory — engrams, learning, and recall — is handled by Datacore's companion server, PLUR (plur_* tools). Run the two side by side: PLUR remembers, Datacore organizes.

Not a RAG system. Not a vector database you have to manage. Just plain-text files and an MCP server.

Quick Start

Install globally:

npm install -g @datacore-one/mcp

Then connect from any MCP-compatible client. On first use, the server creates ~/Datacore/ with:

journal/ — Daily session logs
knowledge/ — Ingested reference material
engrams.yaml — Shared engram store, read and written by the companion PLUR MCP
packs/ — Engram packs used by PLUR
config.yaml — Configuration (all fields optional)
CLAUDE.md, AGENTS.md, .cursorrules, .github/copilot-instructions.md — Editor context files so any AI assistant immediately understands Datacore

Everything is plain text -- no databases, no lock-in.

Connecting

Datacore is a standard MCP server. It works with any client that speaks MCP v1.0+ over stdio or HTTP -- the AI model behind the client does not matter.

Claude Code

Add to .mcp.json in your project root (or ~/.claude.json globally):

{
  "mcpServers": {
    "datacore": {
      "command": "datacore-mcp"
    }
  }
}

Then allow Datacore tools in .claude/settings.json (or .claude/settings.local.json):

{
  "permissions": {
    "allow": [
      "mcp__datacore"
    ]
  },
  "enableAllProjectMcpServers": true
}

This auto-approves all Datacore MCP tools (capture, search, status, etc.) so you don't get prompted on every call. The enableAllProjectMcpServers setting ensures the MCP server defined in .mcp.json is activated automatically.

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "datacore": {
      "command": "datacore-mcp"
    }
  }
}

Cursor / Windsurf / Other MCP Clients

Most MCP-compatible editors use the same config format. Check your editor's MCP documentation for where to place the server config. The command is always datacore-mcp.

HTTP (Remote / Multi-Client)

For shared or remote setups, run in HTTP mode:

datacore-mcp --http

Then point your MCP client to http://127.0.0.1:3100/mcp. See HTTP Transport for options.

Two Modes

Mode	Storage	What You Get
Core (`~/Datacore`)	Flat files	Journal, knowledge, dates, packs
Full (`~/Data`)	Datacore system	+ modules, GTD, spaces, Datacortex

Mode is auto-detected. If you have a full Datacore installation at ~/Data, it uses that. Otherwise it creates a lightweight ~/Datacore directory.

Override with environment variables: DATACORE_PATH (full) or DATACORE_CORE_PATH (core).

Tools (5 core + 3 full-mode)

Datacore exposes productivity tools. Memory — engrams, learning, recall, packs — is provided by the companion PLUR MCP server (plur_* tools), not by Datacore.

Core

Tool	Description
`datacore_capture`	Write a journal entry or knowledge note
`datacore_search`	Search journal and knowledge by keyword or semantic
`datacore_ingest`	Ingest text as a knowledge note
`datacore_status`	System status, counts, actionable recommendations
`datacore_date`	Canonical date operations (today, day-of-week, validate, add/sub, parse, org-stamp)

Modules (full mode only)

Tool	Description
`datacore_modules_list`	List installed modules
`datacore_modules_info`	Detailed info about a module
`datacore_modules_health`	Health check for modules

Tool names use underscores to satisfy the MCP tool-name rule ^[a-zA-Z0-9_-]{1,64}$. Legacy dot-namespaced names (datacore.capture) are still accepted as aliases for backward compatibility.

Prompts

The server provides MCP prompts — workflow templates your AI can discover and use automatically:

Prompt	Description
`datacore-capture-guide`	Capture a journal entry or knowledge note
`datacore-guide`	Complete guide to Datacore tools and workflows

Prompts are the primary way the AI understands Datacore. When your AI connects, it can list available prompts and immediately knows how to capture, search, and organize — and that persistent memory lives in PLUR.

Resources

Resource	Description
`datacore://guide`	Agent workflow reference (markdown)
`datacore://status`	System status summary (JSON)
`datacore://journal/today`	Today's journal entry (markdown)
`datacore://journal/{date}`	Journal entry by date

Memory (via PLUR)

Datacore organizes; PLUR remembers.

Persistent memory — engrams, learning, recall, feedback, and engram packs — lives in the companion PLUR MCP server (plur_* tools). Datacore scaffolds the shared, plain-text data directory (including engrams.yaml and packs/) that PLUR reads and writes, so both servers work against the same ~/Data or ~/Datacore store.

Connect both in your MCP client and your AI gets a second brain (Datacore) plus persistent memory (PLUR). See the PLUR docs for the memory toolset and engram lifecycle.

Upgrading from ≤1.5? The engram engine (learn, inject, recall, promote, feedback, forget, packs, and the engagement/XP layer) moved out of Datacore into PLUR. Install @plur-ai/mcp alongside Datacore to keep that functionality.

Configuration

Environment Variables

Variable	Default	Description
`DATACORE_PATH`	`~/Data`	Full installation path
`DATACORE_CORE_PATH`	`~/Datacore`	Core mode storage path
`DATACORE_TIMEZONE`	System	IANA timezone (e.g., `Europe/Ljubljana`)
`DATACORE_LOG_LEVEL`	`warning`	`debug`, `info`, `warning`, `error`
`DATACORE_CACHE_TTL`	`60`	File cache TTL in seconds
`DATACORE_TRANSPORT`	`stdio`	`stdio` or `http`
`DATACORE_HTTP_PORT`	`3100`	HTTP transport port
`DATACORE_HTTP_HOST`	`127.0.0.1`	HTTP bind address

config.yaml

Create config.yaml in your Datacore directory (or .datacore/config.yaml in full mode):

version: 2
search:
  max_results: 20
  snippet_length: 500        # chars around match
hints:
  enabled: true              # include _hints in tool responses for agent guidance

All fields have defaults -- the file is optional. Memory-related settings (engrams, packs, engagement) are configured in PLUR, not here.

HTTP Transport

For remote or multi-client setups:

DATACORE_HTTP_PORT=8080 datacore-mcp --http

MCP endpoint: POST /mcp
Health check: GET /health
Default bind: 127.0.0.1:3100

Module System (Full Mode)

Full Datacore installations extend the MCP server with module-provided tools. Modules are discovered from .datacore/modules/ and space-scoped directories. Each module can register its own tools under the datacore_[module]_[tool] namespace.