Project Management MCP Server: Connect Assistants to Tasks, Projects, and Time Tracking
A project management MCP server enables AI assistants to interact directly with your tasks, projects, boards, and time tracking. Instead of manually copying information, your AI can read, create, and update project data in real-time through a standardized interface.
What Problems Does a Project Management MCP Server Solve?
Traditional project management requires constant context switching:
Before MCP: Manual Workflows
- Copy task details from project tool to AI chat
- Manually update tasks after AI suggestions
- Switch between tools to check status
- Lose context when moving between applications
- Time-consuming data entry and updates
With MCP: Integrated Workflows
- AI reads tasks directly from your project tool
- AI creates and updates tasks automatically
- Natural language interaction with your data
- Context stays in one place (your AI assistant)
- Automated time tracking and progress updates
Key Capabilities
Corcava's project management MCP server provides comprehensive access to your workspace:
Task Management
- List and search tasks
- Get task details
- Create new tasks
- Update task status and fields
- Delete tasks (with confirmation)
Project Organization
- List projects
- Get project details
- View project members
- Access project settings
Board Workflows
- List workflow boards
- Get board structure
- View columns and states
- Track task movement
Time Tracking
- Start timers on tasks
- Stop timers and log time
- Check current tracking status
- Attach notes to time entries
Example Prompts
Here are real examples of what you can do with Corcava's MCP server:
Weekly Planning
Prompt: "What tasks are due this week, and which ones are blocked?"
What happens:
- AI calls
list_taskswith filters for due dates - AI analyzes tasks and identifies blockers
- AI presents a formatted weekly plan
Create Follow-Up Task
Prompt: "Create a follow-up task to contact Acme Corp next week"
What happens:
- AI calls
create_taskwith title and due date - AI confirms what was created
- You see the new task in Corcava
Start Time Tracking
Prompt: "Start tracking time on the 'Implement login feature' task"
What happens:
- AI finds the task using
list_tasks - AI calls
start_time_trackingwith task ID - Timer starts in Corcava
Status Report
Prompt: "Generate a status report for the Q1 project"
What happens:
- AI calls
get_projectto get project details - AI calls
list_tasksfiltered by project - AI analyzes task status and generates report
How It Works
MCP (Model Context Protocol) is an open standard that enables AI assistants to discover and use tools:
The MCP Flow
- Connect: Your AI client connects to Corcava's MCP server
- Discover: AI automatically discovers available tools (list_tasks, create_task, etc.)
- Interact: You ask questions in natural language
- Execute: AI decides which tools to call and executes them
- Respond: AI presents results in a user-friendly format
Learn more about what MCP is and how MCP architecture works.
Getting Started
Ready to connect your AI assistant to Corcava? Here's what you need:
Quick Setup (5 Minutes)
- Get your API key from Corcava Settings → Integrations
- Add Corcava MCP server to your AI client
- Restart your AI client
- Verify tools are available
- Try your first prompt!
Client-Specific Setup
Choose your AI assistant for detailed setup instructions:
Claude Desktop
Setup guide for macOS, Windows, and Linux
Cursor
IDE-focused setup with workflow examples
Windsurf
Settings UI configuration guide
Continue
SSE transport configuration
Tools Reference
Corcava's MCP server provides a comprehensive set of tools for project management:
Projects
Boards
See the complete tools reference for detailed documentation on each tool.
Use Cases
Explore real workflows you can build with Corcava's MCP server:
Weekly Planning
Generate weekly plans from tasks, identify blockers, and set priorities
Daily Focus
Pick 3 high-impact tasks for today with time-boxed planning
Status Reports
Automatically generate stakeholder-ready status updates
Time Tracking
Start/stop timers and log work summaries
Meeting Notes to Tasks
Extract action items and create follow-up tasks
Sprint Planning
Turn sprint goals into scoped tasks with acceptance criteria
See all use cases and workflows.
Security and Safety
When AI assistants can modify your project data, security is critical:
- API Key Management: Separate keys per client, regular rotation
- Least Privilege: Read-first patterns, confirmation before writes
- Audit Logging: Track all tool calls and changes
- Safe Write Operations: Preview and confirm before create/update/delete
Learn more about MCP security best practices.
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