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MCP Integration (AI Assistants)

NoteDiscovery includes a built-in Model Context Protocol (MCP) server that enables AI assistants like Cursor, Claude Desktop, and other MCP-compatible clients to interact with your notes.

What is MCP?

MCP (Model Context Protocol) is an open standard that allows AI assistants to securely access external tools and data sources. With the NoteDiscovery MCP server, your AI assistant can:

🔍 Search through your notes
📖 Read note contents
🏷️ Browse by tags
📝 Create new notes
✏️ Append to existing notes (journals, logs)
📂 Organize notes (move, rename, folders)
📋 Use templates to create structured notes
🔗 Explore the knowledge graph

Quick Setup

If You Use Docker

Add this to your ~/.cursor/mcp.json (or Claude Desktop config):

{
  "mcpServers": {
    "notediscovery": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i",
        "-e", "NOTEDISCOVERY_URL",
        "-e", "NOTEDISCOVERY_API_KEY",
        "ghcr.io/gamosoft/notediscovery:latest",
        "python", "-m", "mcp_server"
      ],
      "env": {
        "NOTEDISCOVERY_URL": "http://host.docker.internal:8000",
        "NOTEDISCOVERY_API_KEY": ""
      }
    }
  }
}

If You Use Python

Install NoteDiscovery (if not already):

pip install notediscovery
# or from source:
pip install .

Add to your MCP config:

{
  "mcpServers": {
    "notediscovery": {
      "command": "notediscovery-mcp",
      "env": {
        "NOTEDISCOVERY_URL": "http://localhost:8000",
        "NOTEDISCOVERY_API_KEY": ""
      }
    }
  }
}

Running from Source (No Install)

{
  "mcpServers": {
    "notediscovery": {
      "command": "python",
      "args": ["-m", "mcp_server"],
      "cwd": "/path/to/NoteDiscovery",
      "env": {
        "PYTHONPATH": "/path/to/NoteDiscovery",
        "NOTEDISCOVERY_URL": "http://localhost:8000"
      }
    }
  }
}

Note: The PYTHONPATH is required so Python can find the mcp_server module. On Windows, use backslashes: "PYTHONPATH": "C:\\path\\to\\NoteDiscovery"

Configuration

Environment Variables

Variable	Required	Default	Description
`NOTEDISCOVERY_URL`	Yes	`http://localhost:8000`	URL where NoteDiscovery is running
`NOTEDISCOVERY_API_KEY`	If auth enabled	-	API key from `config.yaml`
`NOTEDISCOVERY_TIMEOUT`	No	`30`	Request timeout in seconds
`NOTEDISCOVERY_MAX_RETRIES`	No	`3`	Max retry attempts for failed requests

URL Configuration by Setup

Your Setup	`NOTEDISCOVERY_URL`
Local Python (`run.py`)	`http://localhost:8000`
Docker with `-p 8000:8000`	`http://host.docker.internal:8000`
Docker with `-p 3000:8000`	`http://host.docker.internal:3000`
Remote server	`https://notes.example.com`

Available Tools

The MCP server provides these tools to AI assistants:

Search & Discovery

Tool	Description
`search_notes`	Full-text search across all notes (supports `max_results`)
`list_notes`	List all notes with metadata (supports `max_results`)
`get_note`	Read a specific note's content
`get_recent_notes`	Get recently modified notes (last N days)

Organization

Tool	Description
`list_tags`	List all tags with note counts
`get_notes_by_tag`	Find notes with a specific tag (supports `max_results`)
`get_graph`	Get knowledge graph data

Note Management

Tool	Description
`create_note`	Create or update a note
`append_to_note`	Append content to an existing note (great for journals/logs)
`move_note`	Move or rename a note
`delete_note`	Delete a note
`create_folder`	Create a new folder

Templates

Tool	Description
`list_templates`	List available templates
`get_template`	Get template content
`create_note_from_template`	Create a note from a template with variable substitution

System

Tool	Description
`health_check`	Verify server connectivity

Tool Details

Pagination with `max_results`

Some tools support an optional max_results parameter to limit results for large vaults:

Tool	Parameter	Description
`search_notes`	`max_results`	Limit number of search results
`list_notes`	`max_results`	Limit number of notes returned
`get_notes_by_tag`	`max_results`	Limit number of notes returned

When omitted, all results are returned. This is useful for large note collections where you only need a subset.

Example prompt: "Search for notes about Python, but just show me the first 5 results"

`append_to_note`

Append content to an existing note without overwriting. Perfect for journals, logs, or collecting ideas.

Parameter	Type	Required	Description
`path`	string	Yes	Path to existing note
`content`	string	Yes	Content to append
`add_timestamp`	boolean	No	Add timestamp header before content

Example prompt: "Add this meeting summary to my daily-journal.md with a timestamp"

`move_note`

Move or rename a note to a different location.

Parameter	Type	Required	Description
`old_path`	string	Yes	Current note path
`new_path`	string	Yes	New path (can include folder)

Example prompt: "Move draft.md to published/final-article.md"

`get_recent_notes`

Get recently modified notes. Useful for context about what you've been working on.

Parameter	Type	Required	Default	Description
`days`	integer	No	7	Notes modified in last N days
`limit`	integer	No	10	Max notes to return

Example prompt: "What was I working on this week?"

`create_note_from_template`

Create a new note from a template with variable substitution.

Parameter	Type	Required	Description
`template_name`	string	Yes	Template name (e.g., "meeting-notes")
`note_path`	string	Yes	Path for the new note
`variables`	object	No	Variables to substitute (e.g., `{"project": "Alpha"}`)

Built-in placeholders: {{date}}, {{time}}, {{datetime}}, {{title}}, {{folder}}

Example prompt: "Create a new meeting note for Project Alpha using the meeting-notes template"

Usage Examples

Once configured, you can interact with your notes naturally:

User: "What did I write about Kubernetes?"

AI: Uses search_notes to find relevant notes, then get_note to read them

"I found 3 notes about Kubernetes. In your 'devops/k8s-setup.md' note from last week, you documented..."

User: "Create a new note summarizing our conversation"

AI: Uses create_note to save the summary

"Done! I've created 'meetings/ai-discussion-2024-03-13.md' with the summary."

User: "Show me all notes tagged with #project"

AI: Uses get_notes_by_tag to find them

"You have 7 notes with the #project tag..."

User: "Add this to my daily journal with a timestamp"

AI: Uses append_to_note with add_timestamp: true

"Done! I've appended your entry to 'daily-journal.md' with today's timestamp."

User: "What was I working on last week?"

AI: Uses get_recent_notes with days: 7

"You modified 5 notes in the last week: project-roadmap.md, meeting-notes.md..."

User: "Create a meeting note for the design review using my template"

AI: Uses create_note_from_template with the meeting-notes template

"Created 'meetings/design-review-2024-03-13.md' from your meeting-notes template."

Authentication

If you have authentication enabled in NoteDiscovery:

Generate an API key in config.yaml:

authentication:
  enabled: true
  api_key: "your-secure-api-key-here"

Add the key to your MCP config:

"env": {
  "NOTEDISCOVERY_URL": "http://localhost:8000",
  "NOTEDISCOVERY_API_KEY": "your-secure-api-key-here"
}

Troubleshooting

"Connection refused" error

Ensure NoteDiscovery is running
Check the NOTEDISCOVERY_URL is correct
For Docker: use host.docker.internal instead of localhost

"Not authenticated" error

Check that your API key is correct
Ensure the API key in MCP config matches config.yaml

MCP server not starting

Check Cursor/Claude Desktop logs for errors
Try running manually: python -m mcp_server
Verify Python 3.10+ is installed

Verify connectivity manually

# Set environment variables
export NOTEDISCOVERY_URL=http://localhost:8000
export NOTEDISCOVERY_API_KEY=your-key

# Run the MCP server (Ctrl+C to stop)
python -m mcp_server

Then in another terminal:

# Test the health endpoint directly
curl http://localhost:8000/health

Architecture

┌─────────────────┐     stdio (JSON-RPC)     ┌─────────────────┐
│   AI Assistant  │ ◄──────────────────────► │   MCP Server    │
│ (Cursor/Claude) │                          │ (notediscovery- │
└─────────────────┘                          │      mcp)       │
                                             └────────┬────────┘
                                                      │
                                                      │ HTTP/REST
                                                      ▼
                                             ┌─────────────────┐
                                             │  NoteDiscovery  │
                                             │     Server      │
                                             │  (port 8000)    │
                                             └─────────────────┘
                                                      │
                                                      ▼
                                             ┌─────────────────┐
                                             │   Your Notes    │
                                             │  (./data/*.md)  │
                                             └─────────────────┘

The MCP server is a separate process that:

Communicates with AI assistants via stdio (stdin/stdout)
Translates MCP requests into HTTP API calls
Returns results back to the AI assistant

Your notes stay local. The MCP server just provides a bridge for AI access.

Privacy & Security

Notes stay local: The MCP server only accesses notes through NoteDiscovery's API
No external calls: No data is sent to external services
API key protected: Use authentication to control access
Read what you allow: AI can only access notes NoteDiscovery serves

File Structure

NoteDiscovery/
├── mcp_server/
│   ├── __init__.py      # Package entry point
│   ├── __main__.py      # Module runner
│   ├── server.py        # MCP protocol implementation
│   ├── client.py        # HTTP client for NoteDiscovery API
│   ├── config.py        # Configuration management
│   └── tools.py         # Tool definitions
└── ...

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