Tempo Filler MCP Server▌
by TRANZACT
Tempo Filler MCP Server: let AI assistants access Tempo for Jira to retrieve, create, and manage Jira worklogs and strea
A Model Context Protocol server enabling AI assistants to interact with Tempo's time tracking system in JIRA for worklog retrieval, creation, and management.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Development teams using JIRA and Tempo for time tracking
- / Project managers monitoring team time entries
- / Consultants logging billable hours across multiple projects
capabilities
- / Retrieve worklogs from Tempo time tracking
- / Create new time entries in JIRA projects
- / Perform bulk worklog operations
- / View work schedules in calendar format
- / Display timesheet grids with coverage tracking
- / Manage time tracking data through conversational interface
what it does
Connects AI assistants to Tempo time tracking in JIRA for viewing, creating, and managing worklogs with visual calendar and timesheet interfaces.
about
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.
how to install
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.
license
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.
readme
⏰ Tempo Filler MCP Server
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.
🖼️ Visual UI with MCP Apps
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!
Timesheet Grid View
Ask for your logged hours and see them in a familiar Tempo-style pivot table:

Features:
- Issues as rows, time periods as columns
- Coverage-aware coloring (green = full, yellow = under, red = gap)
- Zoom toggle: Days / Weeks / Months
- Total row with logged/required hours comparison
Schedule Calendar View
Check your work schedule with a visual calendar:

Features:
- Month grid with working days (green) and non-working days (gray)
- Shows required hours per day
- Holiday and weekend awareness
- Summary with total working days and required hours
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.
🚀 Quick Start
Install in VS Code
Install in Claude Desktop
- Click the button above to download the desktop extension (
.dxtfile) - Open Claude Desktop and go to Settings → Extensions
- Drag the downloaded
.dxtfile into the extensions panel to install- If dragging doesn't work: Click Advanced Settings → Install Extension and select the downloaded file
- Fill in the Tempo Base URL and PAT in the environment variables section
- Don't forget to enable it!
Install Manually on your favorite AI Assistant
{
"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"
}
}
}
}
💬 Real Usage Example
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:
- 3 Tool Calls:
get_worklogs→get_schedule→bulk_post_worklogs - Smart Pattern Recognition: Automatically identified PROJ-1234 from September data
- Schedule Awareness: Only filled working days, skipped weekends automatically
- Bulk Operations: Created 23 worklog entries in a single API call
- Error-Free Execution: 100% success rate with proper validation
- Natural Language: No need to remember issue keys, dates, or tool syntax
⏱️ Time Saved: This single natural language request triggered 3 MCP tool calls and replaced hours of manual timesheet entry!
🛠️ How This Was Built
This MCP server was built in just 3 hours using AI-powered development tools, demonstrating the power of modern AI-assisted coding:
Development Timeline
-
Specification Phase
- Created the complete technical specification using GitHub Copilot with Claude Sonnet 4
- Defined all API endpoints, data structures, and tool interfaces
- Refined requirements through iterative conversation
-
Implementation Phase
- Used VS Code with Claude Code to one-shot the entire implementation
- Generated complete TypeScript codebase, tool implementations, and client logic
- Implemented all core functionality in a single AI-assisted session
-
Refinement Phase
- Switched back to GitHub Copilot with Claude Sonnet 4 after hitting usage limits in Claude Code
- Fixed API payload formatting and authentication issues
- Debugged and polished the Tempo API integration
Key Success Factors
- Clear specification first: Having a detailed spec enabled effective one-shot implementation
- AI tool synergy: Different AI tools excelled at different phases of development
- Iterative refinement: Quick feedback loops with AI assistants for debugging
This project showcases how AI-powered development can dramatically accelerate the creation of robust, production-ready tools.
✨ Features
- Get Worklogs: Retrieve worklogs for users with date range and issue filtering
- Create Worklogs: Add single worklog entries with automatic issue resolution
- Bulk Operations: Create multiple worklog entries efficiently using concurrent processing
- Delete Worklogs: Remove existing worklog entries
- Get Schedule: Retrieve work schedule with working/non-working day information
- Visual UIs: Rich calendar and timesheet grid views via MCP Apps
- Resource Access: Browse worklog data and recent issues
- Prompt Templates: Generate analysis prompts for worklog data
📦 Installation
Prerequisites
- Node.js (version 18 or higher)
- A JIRA instance with Tempo Timesheets plugin installed
- Personal Access Token for your JIRA account
NPX (Recommended)
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.
Development Setup (Source)
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
⚙️ Configuration
The server requires environment variables for authentication and configuration:
Required Environment Variables
TEMPO_BASE_URL: Your JIRA instance URL (e.g.,https://jira.company.com)TEMPO_PAT: Personal Access Token for authentication
Optional Environment Variables
TEMPO_DEFAULT_HOURS: Default hours per workday (default: 8)
Creating a Personal Access Token (PAT)
- Log into your JIRA instance
- Go to Profile → Personal Access Tokens
- Click Create token
- Give it a name (e.g., "Tempo MCP Server")
- Set appropriate permissions (read/write access to issues and worklogs)
- Copy the token value for use in
TEMPO_PAT
🛠️ Available Tools
1. get_worklogs - Retrieve Time Logs
Retrieve worklogs for a date range with optional filtering. In MCP Apps-compatible hosts, displays an interactive timesheet grid.
FAQ
- What is the Tempo Filler MCP Server MCP server?
- Tempo Filler MCP Server is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Tempo Filler MCP Server?
- This profile displays 52 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
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
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
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
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ 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.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.7★★★★★52 reviews- ★★★★★Emma Ghosh· Dec 20, 2024
We evaluated Tempo Filler MCP Server against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Ishan Ramirez· Dec 12, 2024
Useful MCP listing: Tempo Filler MCP Server is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Emma Gill· Dec 4, 2024
Tempo Filler MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Li Patel· Nov 23, 2024
Tempo Filler MCP Server is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Sofia Perez· Nov 11, 2024
We wired Tempo Filler MCP Server into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Sofia Jackson· Nov 3, 2024
Strong directory entry: Tempo Filler MCP Server surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Ishan Abbas· Oct 18, 2024
I recommend Tempo Filler MCP Server for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Ganesh Mohane· Oct 14, 2024
Strong directory entry: Tempo Filler MCP Server surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Emma Srinivasan· Oct 14, 2024
We evaluated Tempo Filler MCP Server against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Sofia Choi· Oct 2, 2024
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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