Lucen Track
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The Lucen Track MCP allows you to log time entries and make reports from your favorite agent
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- Productivity, Project Management
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Connect your AI tool to Lucen Track using the Model Context Protocol (MCP). Once connected, your tool can read and write time entries, manage timers, and pull reports based on your account permissions.
Learn how to connect your favorite AI tools to Lucen Track to automate your time tracking, how to solve the most common connection issues, and the frequently asked questions on this integration and how it works.
If you have any other questions, comments or suggestions, feel free tocontact us!
- Claude Code
- Claude Desktop
- Cursor
- VS Code (GitHub Copilot)
- Windsurf
- ChatGPT
- Codex
- Other tools
claude mcp add --transport http lucen-track https://track-api.lucensoftware.com/mcp
Then authenticate by running /mcp in Claude Code and following the OAuth flow.
For a richer experience, install theLucen Track plugin for Claude Code. It bundles the MCP server with slash commands (/log-time, /track-timer, /fix-entry, /time-report) for common workflows.
Using --scope flags for different installation scopes
- --scope local(default): Available only to you in the current project
- --scope project: Shared with your team via.mcp.json
- --scope user: Available to you across all projects
Use /mcp to list and manage MCP servers, and /context to see token usage per server.
- OpenSettings→Connectors
- ClickAdd Connectorand enter the URL:
https://track-api.lucensoftware.com/mcp
- Complete the OAuth flow to connect your Lucen Track workspace
Note: Remote MCP servers in Claude Desktop are configured through Settings → Connectors, not the claude_desktop_config.json file. Available on Pro, Max, Team, and Enterprise plans.
- OpenCursor Settings→MCP→Add new global MCP server
- Paste the following configuration:
{ "mcpServers": { "lucen-track": { "url": "https://track-api.lucensoftware.com/mcp" } } }
- Save and restart Cursor. The first time you use a Lucen Track tool, complete the OAuth flow.
To share the Lucen Track MCP configuration with your team, create a.cursor/mcp.json file in your project root with the same server configuration shown above.
- Create a.vscode/mcp.json file in your workspace:
{
"servers": {
"lucen-track": {
"type": "http",
"url": "https://track-api.lucensoftware.com/mcp"
}
}
}
- Open the Command Palette (Cmd+Shift+P/Ctrl+Shift+P) and runMCP: List Servers
- Start the Lucen Track server and complete the OAuth flow when prompted
To configure Lucen Track MCP across all workspaces, run MCP: Open User Configuration from the Command Palette and add the server there.
- OpenWindsurf Settings(Cmd+,on Mac) → search forMCP
- ClickView raw configto openmcp_config.json
- Add the Lucen Track server configuration:
{ "mcpServers": { "lucen-track": { "serverUrl": "https://track-api.lucensoftware.com/mcp" } } }
- Save and restart Windsurf. Complete the OAuth flow when prompted.
- Go tochatgpt.com/#settings/Connectors(requires login)
- ClickAdd Connectorand enter the URL:
- Complete the OAuth flow to connect your Lucen Track workspace
MCP connectors in ChatGPT require a Plus, Team, or Enterprise plan.
For more details, see theCodex MCP documentation.
- Add the Lucen Track server to your Codex configuration at~/.codex/config.toml:
[mcp_servers.lucen-track] url = "https://track-api.lucensoftware.com/mcp"
- Complete the OAuth flow to connect your Lucen Track workspace.
To share the Lucen Track MCP configuration with your team, create a.codex/config.toml file in your project root with the same server configuration.
If your AI tool isn't listed above but supports MCP, you can connect using one of these:
Most MCP clients accept a JSON configuration. Use the appropriate format for your tool:
{ "mcpServers": { "lucen-track": { "url": "https://track-api.lucensoftware.com/mcp" } } }
{ "mcpServers": { "lucen-track": { "command": "npx", "args": ["-y", "mcp-remote", "https://track-api.lucensoftware.com/mcp"] } } }
Use the STDIO configuration if your tool doesn't support remote HTTP connections directly. Requires Node.js installed on the local machine.
1) My tool doesn't support remote MCP servers
Some MCP clients only support local stdio servers. You can still connect to Lucen Track MCP using themcp-remotebridge:
{ "mcpServers": { "lucen-track": { "command": "npx", "args": ["-y", "mcp-remote", "https://track-api.lucensoftware.com/mcp"] } } }
Requires Node.js installed on the local machine.
- Make sure you complete the OAuth flow when prompted
- Try disconnecting and reconnecting — look for a "Clear authentication" or "Disconnect" option in your tool's MCP settings
- If you usedmcp-remote, delete the cached token under~/.mcp-auth/and restart the client
- Verify you have the correct permissions in the Lucen Track workspace you're trying to access
3) The AI can't find my project or todo
The MCP server only sees data your authenticated user has visibility to in Lucen Track. If a project, todo, or tag doesn't appear:
- Confirm you're logged in to the correct Lucen Track account
- Check the project is active and you're a member
- For todos: ensure the integration ID (Jira/Asana reference) is exactly as it appears in the linked system
Check your tool's documentation for how to add a remote MCP server. Most tools accept either a URL directly or a JSON configuration. If your tool doesn't support MCP yet, consider reaching out to the developers to request MCP support.
Can I use Lucen Track MCP without a human in the loop?
Lucen Track MCP requires user-based OAuth authentication and does not currently support bearer-token access. This means a user must complete the OAuth flow to authorize access, which may not be suitable for fully automated workflows or cloud-based agents that run without human interaction.
If you need headless or automated access, you can call the underlyingLucen Track REST APIdirectly with an OAuth token, though MCP is the recommended path for AI-assistant use cases.
Is my time tracking data used to train AI?
Lucen Track never uses your tracked data to train AI models. The data sent to the AI tool you connect (Claude, ChatGPT, etc.) is governed by that tool's terms — for Claude, Anthropic's commercial terms exclude data passed through the Connectors Directory from model training.
The server exposes 11 tools covering reads (projects, todos, tags, entries, summaries, reports, active timer state) and writes (create / update time entries, start / stop timers). It does not expose administrative operations like creating projects, inviting users, or changing billing settings.
From inside your AI tool's MCP / Connectors panel. Revoking the OAuth token immediately stops further data flow.
If you're integrating Lucen Track MCP into your own application or building a custom AI tool, see theMCP client documentationfor step-by-step instructions on implementing OAuth and connecting to a remote MCP server. The Lucen Track endpoint follows the standard MCP OAuth discovery flow.
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