@mudravaorg/mcp-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| PIXELFIXER_API_URL | No | PixelFixer instance URL | http://localhost:3000 |
| PIXELFIXER_API_TOKEN | Yes | Personal API token (starts with pf_) |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| init_sessionA | Initialize the MCP session. Call this FIRST before any other tool. Auto-discovers your team/project from the API token and returns the AI task queue. If you have exactly one team and one project, they are auto-selected for all subsequent calls (no need to pass teamId/projectId). If you have multiple teams or projects, call set_context afterward to select which one to work with. |
| set_contextA | Set or change the active team and/or project for this session. Use this after init_session when you have multiple teams/projects. Once set, all subsequent tool calls will use these IDs automatically — no need to pass teamId/projectId every time. |
| list_teamsA | List all teams the authenticated user belongs to. |
| list_projectsB | List all projects in a team. |
| get_projectB | Get details of a specific project including its GitHub connection. |
| list_team_membersB | List all members of a team. |
| list_tasksA | List all tasks in a project (compact summaries). Use get_task for full details of a specific task. |
| get_taskA | Get full details of a task: description, metadata, screenshot, page URL, CSS selector, browser info, console/network errors, comments, AI status. Accepts taskId OR taskNumber. |
| create_taskA | Create a new task. Requires title and columnId. IMPORTANT: title and description MUST be in English. |
| update_taskA | Update task properties. Do NOT use this to move columns — use start_task/complete_ai_task instead. Accepts taskId OR taskNumber. IMPORTANT: title/description in English. |
| move_taskA | Move a task to a different kanban column. Only use when explicitly asked — start_task and complete_ai_task handle column moves automatically. |
| search_tasksA | Search tasks with filters. Returns compact summaries. Use get_task for full details. |
| add_commentB | Add a comment to a task. Call AFTER making changes and BEFORE complete_ai_task. IMPORTANT: content in English. |
| list_commentsA | List all comments on a task. |
| list_columnsB | List all kanban columns in a project. |
| get_github_contextB | Get the GitHub repository connection for a project. Returns null if no repo is connected. |
| get_repo_treeC | Browse the file tree of the connected GitHub repository. |
| get_file_contentA | Read a file from the connected GitHub repository. |
| create_pull_requestA | Create a branch and pull request. Call BEFORE commit_files. IMPORTANT: all text in English. |
| commit_filesA | Commit files to a branch. Call AFTER create_pull_request. Max 50 files. IMPORTANT: commit message in English. |
| start_taskA | Start working on an AI task. Moves task to In Progress, sets AI status to PROCESSING, returns full context (task, comments, GitHub info, columns). Accepts taskId OR taskNumber. Call this FIRST for every AI task. |
| complete_ai_taskA | Report the result of AI work. Auto-moves task to Review column. Call AFTER add_comment. IMPORTANT: message in English. Status defaults to COMPLETED if omitted. |
| list_ai_queueA | List tasks queued for AI processing (compact summaries). Supports optional priority and tag filters. Use start_task on each to begin work. |
| batch_get_tasksA | Get full details of multiple tasks in a single call. Accepts an array of task numbers. More efficient than calling get_task multiple times. |
| batch_start_tasksA | Start multiple AI tasks at once. Sets each to IN_PROGRESS / PROCESSING. Returns compact results. More efficient than calling start_task multiple times. |
| batch_complete_tasksA | Complete multiple AI tasks in a single call. Each entry can have its own message, prUrl, and commitHash. Status defaults to COMPLETED. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 26 tools
Most tools map to distinct actions/resources, but get_project's description already includes GitHub connection info, overlapping with get_github_context; list_tasks and list_ai_queue also require careful reading. The batch variants are clearly labeled as bulk versions, reducing confusion.
All tools use a consistent lowercase snake_case verb_noun pattern such as init_session, list_tasks, complete_ai_task, and batch_get_tasks. The pattern is predictable across session, task, comment, and GitHub operations.
At 26 tools, the server exceeds the 25-tool threshold and feels heavy. Several batch_* variants add redundant surface area that could be handled with optional parameters on the singular tools.
The core lifecycle is well covered: session/context setup, task CRUD and search, comments, kanban states, AI queue handling, GitHub file browsing, and PR creation/commit. Minor gaps such as deleting tasks, updating comments, or checking PR status are workarounds rather than dead ends.