datacore-mcp
OfficialA plain-text second brain for AI assistants — journal, knowledge, and productivity tools over MCP.
Capture: Write journal entries or knowledge notes with titles, content, and tags.
Search: Find notes by keyword or semantic similarity, scoped to journal, knowledge, or both.
Ingest: Import external text as structured knowledge notes.
Date operations: Get today’s date, day-of-week, validate dates, add/subtract days, compute date differences, parse relative expressions (e.g., “next Monday”), and format org‑mode timestamps.
System status: View note counts, module health, and update information.
Module management (full mode): List, inspect, and health‑check installed modules.
Prompts and resources: Guided workflows, status summaries, journal entries by date, and agent workflow references.
Plain‑text storage: All data kept in human‑readable files under
~/Datacoreor~/Data.Companion integration: Works with the PLUR MCP server for persistent memory (engrams, recall, learning).
Flexible deployment: Runs locally via stdio or remotely over HTTP for multi‑client setups.
@datacore-one/mcp
A plain-text second brain for AI assistants — journal, knowledge, and productivity tools over MCP.
Why
AI assistants are great at reasoning but have nowhere to put what matters: your decisions, your notes, your day.
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.
Related MCP server: OpenMemory
Quick Start
Install globally:
npm install -g @datacore-one/mcpThen connect from any MCP-compatible client. On first use, the server creates ~/Datacore/ with:
journal/— Daily session logsknowledge/— Ingested reference materialengrams.yaml— Shared engram store, read and written by the companion PLUR MCPpacks/— Engram packs used by PLURconfig.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 --httpThen 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 ( | Flat files | Journal, knowledge, dates, packs |
Full ( | 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 |
| Write a journal entry or knowledge note |
| Search journal and knowledge by keyword or semantic |
| Ingest text as a knowledge note |
| System status, counts, actionable recommendations |
| Canonical date operations (today, day-of-week, validate, add/sub, parse, org-stamp) |
Modules (full mode only)
Tool | Description |
| List installed modules |
| Detailed info about a module |
| 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 |
| Capture a journal entry or knowledge note |
| 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 |
| Agent workflow reference (markdown) |
| System status summary (JSON) |
| Today's journal entry (markdown) |
| 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/mcpalongside Datacore to keep that functionality.
Configuration
Environment Variables
Variable | Default | Description |
|
| Full installation path |
|
| Core mode storage path |
| System | IANA timezone (e.g., |
|
|
|
|
| File cache TTL in seconds |
|
|
|
|
| HTTP transport port |
|
| 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 guidanceAll 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 --httpMCP endpoint:
POST /mcpHealth check:
GET /healthDefault 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.
License
MIT
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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