About ithura
ithura is an MCP server for managing work in an Ithura project workspace. Teams can let MCP clients read and update tasks, projects, sprints, modules, and wiki pages through structured JSON tools.
Key features
- 01Read and update projects
- 02Create, update, and delete tasks
- 03Manage sprints and task membership
- 04Create and manage modules
- 05Search workspace content
- 06Manage labels and task comments
Use cases
- 01Check tasks remaining in a sprint
- 02Create a task for a reported bug
- 03Summarize tasks completed during a period
- 04Search work across a workspace
MCP support
Connects MCP clients to an Ithura workspace using an API token and workspace slug. It exposes 23 tools for reading and writing workspace data.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y ithura-mcpITHURA_API_KEYSecretWorkspace API token, created under Settings > API tokens. Carries the permissions of the member who created it.ITHURA_WORKSPACE_SLUGThe workspace slug, as it appears in your Ithura URL.ITHURA_API_URLAPI base URL. Defaults to https://api.ithura.com; set this when self-hosting.Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
23Saved tool list · updated 3w ago
This tool takes no parameters.
Details
From the project READMEIthura MCP server
A Model Context Protocol server for Ithura, a quiet project management workspace for deliberate teams.
Point Claude, Cursor, or any MCP client at your Ithura workspace and let it read and write real work: tasks, sprints, projects, modules, wiki pages, and intake.
"What is left in the current sprint?"
"Create a task for the login timeout bug and put it in this sprint."
"Summarise every task that moved to Done this week."
Listed in the official MCP Registry
as com.ithura/mcp.
Install
No install step. Point your MCP client at npx:
npx ithura-mcp
Claude Desktop / Claude Code
Add to your MCP settings (claude_desktop_config.json, or .mcp.json in a
project for Claude Code):
{
"mcpServers": {
"ithura": {
"command": "npx",
"args": ["-y", "ithura-mcp"],
"env": {
"ITHURA_API_KEY": "your-api-token",
"ITHURA_WORKSPACE_SLUG": "your-workspace"
}
}
}
}
Cursor
~/.cursor/mcp.json takes the same block.
Configuration
| Variable | Required | Default | Notes |
|---|---|---|---|
ITHURA_API_KEY | yes | Workspace API token, from Settings > API tokens | |
ITHURA_WORKSPACE_SLUG | yes | The slug in your workspace URL | |
ITHURA_API_URL | no | https://api.ithura.com | Point at your own host when self-hosting |
Create the token in Ithura under Settings > API tokens. It carries the permissions of the member who created it, so create it as a user whose access matches what you want the agent to have.
Tools
23 tools across the work graph:
| Area | Tools |
|---|---|
| Projects | list_projects, get_project, create_project, update_project |
| Tasks | list_issues, get_issue, create_issue, update_issue, delete_issue |
| Comments | list_issue_comments, add_issue_comment |
| Sprints | list_cycles, create_cycle, add_issues_to_cycle, remove_issue_from_cycle |
| Modules | list_modules, create_module, add_issues_to_module, delete_module |
| Metadata | list_states, list_labels, create_label |
| Search | search_workspace |
Every tool returns JSON, so the model sees real field values rather than prose.
Notes
- The API noun for a work item is
issuein the HTTP API; the product calls them tasks. The tool names follow the API. - Writes are real. Consider a token scoped to a member with limited project access if you want the agent kept to a corner of the workspace.
- Self-hosting: set
ITHURA_API_URLto your instance and everything else works unchanged.
Links
- Ithura: https://ithura.com
- Documentation: https://ithura.com/docs
- API reference: https://ithura.com/docs/integrations
License
MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.