AI COLLABORATION MCP SERVER TOOLS

28 tools from the AI Collaboration MCP Server MCP Server, categorised by risk level.

View the AI Collaboration MCP Server policy →

// ALL 28 AI COLLABORATION MCP SERVER TOOLS

READ 8 tools

Read ask_question Ask a question about a task Read get_all_tasks Get all tasks in the system Read get_loop_status Get the current status of the autonomous loop Read get_project_plan Get the current active project plan Read get_project_state Get current project state Read get_task_status Get status of a specific task Read list_tickets List tickets with optional filtering Read status Get current system status

WRITE 16 tools

Write answer_question Answer a previously asked question Write create_mission Create a new mission Write create_project_plan Create a comprehensive project plan with multiple phases Write create_ticket Create a new ticket Write diagnose_tasks Diagnose task state discrepancies between project state and actual tasks Write generate_context_summary Generate a summary of current project context Write generate_report Generate a project status report Write init Initialize agent with role-based autonomous workflow Write ping Simple ping to test server connectivity Write review_work Submit a review of submitted work Write send_batch_directives Send multiple task directives at once. Use this to queue up multiple tasks for efficient workflow. Write send_directive Send a task directive to the development team. Can create single or batch tasks with dependencies. Write submit_work Submit completed work for review Write update_plan_progress Update project plan progress when phase is complete Write update_project_state Update the state of a project component Write update_ticket Update an existing ticket

DESTRUCTIVE 1 tools

Destructive reset_task_dependencies Reset task dependencies for tasks that are blocked by completed/missing tasks

EXECUTE 3 tools

Execute start_autonomous_loop Start an autonomous work loop that continuously checks for and processes work Execute stop_autonomous_loop Stop the autonomous work loop Execute stop_autonomous_work Stop autonomous work mode

// FAQ

How many tools does the AI Collaboration MCP Server MCP server have? +

The AI Collaboration MCP Server MCP server exposes 28 tools across 4 categories: Read, Write, Destructive, Execute.

How do I enforce policies on AI Collaboration MCP Server tools? +

Route the AI Collaboration MCP Server server through the PolicyLayer gateway. Define allow, deny, or approval rules per tool in the dashboard; they are enforced on every call before it reaches the server.

What risk categories do AI Collaboration MCP Server tools fall into? +

AI Collaboration MCP Server tools are categorised as Read (8), Write (16), Destructive (1), Execute (3). Each category has a recommended default policy.

Enforce policy on every AI Collaboration MCP Server tool call.

Start from AI Collaboration MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

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