by TRANZACT
Tempo Filler MCP Server: let AI assistants access Tempo for Jira to retrieve, create, and manage Jira worklogs and strea
Connects AI assistants to Tempo time tracking in JIRA for viewing, creating, and managing worklogs with visual calendar and timesheet interfaces.
Tempo Filler MCP Server is an official MCP server published by TRANZACT that provides AI assistants with tools and capabilities via the Model Context Protocol. Tempo Filler MCP Server: let AI assistants access Tempo for Jira to retrieve, create, and manage Jira worklogs and strea It is categorized under productivity.
You can install Tempo Filler MCP Server in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
ISC
Tempo Filler MCP Server is released under the ISC license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
We evaluated Tempo Filler MCP Server against two servers with overlapping tools; this profile had the clearer scope statement.
Useful MCP listing: Tempo Filler MCP Server is the kind of server we cite when onboarding engineers to host + tool permissions.
Tempo Filler MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Tempo Filler MCP Server is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
We wired Tempo Filler MCP Server into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Strong directory entry: Tempo Filler MCP Server surfaces stars and publisher context so we could sanity-check maintenance before adopting.
I recommend Tempo Filler MCP Server for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Strong directory entry: Tempo Filler MCP Server surfaces stars and publisher context so we could sanity-check maintenance before adopting.
We evaluated Tempo Filler MCP Server against two servers with overlapping tools; this profile had the clearer scope statement.
Tempo Filler MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
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A Model Context Protocol (MCP) server for managing Tempo worklogs in JIRA. This server enables AI assistants to interact with Tempo's time tracking system, allowing for worklog retrieval, creation, bulk operations, and management.
TempoFiller now supports MCP Apps - rendering rich visual interfaces directly in compatible AI chat clients like Claude Desktop. Instead of just text responses, you get interactive calendar and timesheet views!
Ask for your logged hours and see them in a familiar Tempo-style pivot table:

Features:
Check your work schedule with a visual calendar:

Features:
Note: Visual UIs render in MCP Apps-compatible hosts (Claude Desktop, VS Code). CLI hosts receive the same structured data, which the AI formats conversationally.
.dxt file).dxt file into the extensions panel to install
{
"mcpServers": {
"tempo-filler": {
"command": "npx",
"args": ["@tranzact/tempo-filler-mcp-server"],
"env": {
"TEMPO_BASE_URL": "https://your-jira-instance.com",
"TEMPO_PAT": "your-personal-access-token"
}
}
}
}
Here's an actual conversation showing how natural and powerful the interaction can be:
👤 User:
fill my october hours with the same project from september
🤖 AI Assistant:
I'll help you fill your October hours with the same project from September. Let me first check your September worklogs to understand the pattern, then fill October accordingly.
🔧 mcp_tempo-filler-_get_worklogs({
"startDate": "2025-09-01",
"endDate": "2025-09-30"
})
Perfect! I can see you worked on PROJ-1234 (Tempo MCP Server) for 200 hours in September. Now let me get your October work schedule to see which days need to be filled.
🔧 mcp_tempo-filler-_get_schedule({
"startDate": "2025-10-01",
"endDate": "2025-10-31"
})
Excellent! I now have all the information needed. Let me fill all 23 working days in October with the Tempo MCP Server project using 8 hours per working day.
🔧 mcp_tempo-filler-_bulk_post_worklogs({
"billable": true,
"worklogs": [
{"issueKey": "PROJ-1234", "hours": 8, "date": "2025-10-01", "description": "Tempo MCP Server development"},
{"issueKey": "PROJ-1234", "hours": 8, "date": "2025-10-02", "description": "Tempo MCP Server development"},
// ... 21 more entries for all working days
]
})
✅ October Hours Filled Successfully
- Project: PROJ-1234 (Tempo MCP Server)
- Total Hours: 184 hours across 23 working days
- Hours per Day: 8 hours (matching your standard work schedule)
- Status: All entries created successfully with no failures
Tool Calls Made:
get_worklogs- Retrieved September pattern (PROJ-1234, 200h)get_schedule- Found 23 working days in October (184h capacity)bulk_post_worklogs- Created 23 entries in one operationYour October timesheet is now complete and matches the same project pattern you used in September!
🎯 What Happened Here:
get_worklogs → get_schedule → bulk_post_worklogs⏱️ Time Saved: This single natural language request triggered 3 MCP tool calls and replaced hours of manual timesheet entry!
This MCP server was built in just 3 hours using AI-powered development tools, demonstrating the power of modern AI-assisted coding:
Specification Phase
Implementation Phase
Refinement Phase
This project showcases how AI-powered development can dramatically accelerate the creation of robust, production-ready tools.
The easiest way to use the server is with npx - no installation required:
npx @tranzact/tempo-filler-mcp-server
Just configure your AI assistant to use npx @tranzact/tempo-filler-mcp-server as the command.
For development or customization:
Clone the repository:
git clone https://github.com/TRANZACT/tempo-filler-mcp-server
cd TempoFiller
Install dependencies and build:
npm install && npm run build
The server requires environment variables for authentication and configuration:
TEMPO_BASE_URL: Your JIRA instance URL (e.g., https://jira.company.com)TEMPO_PAT: Personal Access Token for authenticationTEMPO_DEFAULT_HOURS: Default hours per workday (default: 8)TEMPO_PATget_worklogs - Retrieve Time LogsRetrieve worklogs for a date range with optional filtering. In MCP Apps-compatible hosts, displays an interactive timesheet grid.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.