How to Work with Multiple AI Agents (Claude Code, Antigravity, Cursor) on the Same Project Without Chaos

The New Reality: Developing with Multiple AI Tools Simultaneously

The era where a developer relied on a single AI assistant in a lone browser tab is firmly behind us. Today, seasoned engineers, solo founders, and vibe coders alike leverage an entire arsenal of specialized AI tools, each excelling at a specific stage of software development:

• Cursor: The premier choice for fast in-editor UI modifications, intelligent code completion, and visual frontend tweaks.
• Claude Code: Anthropic's powerful terminal agent, tailored for autonomous backend implementation, deep filesystem tasks, sweeping refactorings, and running test suites directly in the console.
• Google Antigravity: The advanced assistant engineered for deep architectural reasoning, multi-step strategic planning, and rigorous codebase exploration.

On top of this diversity comes human collaboration: you might work alongside a cofounder or an external contributor. You may favor the velocity of Claude Code in the terminal, while your teammate leans into the visual ergonomics of Cursor.

While this multi-tool flexibility is immensely powerful, in practice it rapidly triggers a crippling bottleneck: the chaos of fragmented context.

The Problem of Isolated Silos: When Agents Clash Head-on

Every AI coding tool has attempted to solve project memory independently, introducing proprietary formats or isolated local conventions:

• Cursor reads rules from .cursorrules or the .cursor/rules/ directory.
• Claude Code looks for instructions in the project root's CLAUDE.md file.
• Other tools rely on their own internal system prompts or store conversation histories in private, disconnected clouds.

The outcome is a total communication breakdown across tools. No agent knows what another agent executed ten minutes ago. Here are some of the frequent conflicts that emerge in an uncoordinated multi-agent codebase:

1. Mismatched Conventions and Libraries: If this morning you established in Claude Code that all styling must use Tailwind utility classes, this afternoon Cursor might scaffold a new component using CSS Modules or separate stylesheet files simply because it never saw the decision made in the terminal.
2. Accidental Overwrites and Regressions: An agent unaware that a peer modified the database schema may regenerate old data models, silently breaking working production code.
3. Duplicated Work: Without shared visibility, two assistants can easily end up tackling the same feature in fundamentally incompatible ways.

The Universal Solution: Model Context Protocol (MCP) as a Shared Bridge

To collaborate smoothly with multiple agents on the same repository, you need a coordination layer that is entirely tool-agnostic. You need a platform that favors no single assistant over another, but instead speaks a universal standard that every premier tool understands.

That universal standard is here: the Model Context Protocol (MCP), an open specification created to let AI agents securely access data and tools outside their sandbox.

This is where fanTask comes into play. fanTask is an AI-native project and task tracker exposed via MCP, engineered specifically as a shared meeting ground for humans and autonomous AI assistants.

With fanTask, Claude Code, Cursor, and Google Antigravity all connect to the exact same centralized source of truth. Memory silos disappear, and agents no longer rely on brittle, divergent local files.

The Two Pillars of Seamless Multi-Agent Collaboration in fanTask

fanTask orchestrates multi-agent workflows through two concrete architectural differentiators, built from the ground up for hybrid human-AI collaboration:

1. The Persistent Project-Level "AI Context" Field

Rather than maintaining three separate instruction files, you articulate your core guidelines once, in the AI Context field inside fanTask:

• System architecture and settled tech stacks (e.g.: "SvelteKit with Tailwind; no additional CSS libraries permitted").
• Known gotchas and validated fixes from prior debugging cycles.
• Verified build and test commands.

Whichever agent you fire up — Claude Code in the CLI, Antigravity, or Cursor — each automatically reads the shared project context directly from fanTask at the start of its session.

Within milliseconds, every agent receives the identical, up-to-date directive directly from the server. The rules survive every session restart and remain uniform across all tools.

2. The Synchronized Backlog Shared by All Agents

The second pillar is active task management. In fanTask, all agents and human team members work from the same live task board using native MCP tools:

• No Overlapping Work: When Claude Code picks up a task, it transitions it to in_progress. If you open Cursor or a teammate checks active tasks, everyone sees immediately that the module is being worked on and picks a different ticket from the backlog.
• Transparent Tool Handoffs: You can prompt Antigravity to architect a database schema and break it into subtasks directly on the board. Next, you can switch to Claude Code to run the database migrations in your terminal, and finally hop into Cursor to wire up the frontend UI. Each agent finds structured audit notes left by the previous tool directly on the ticket.
• Unified Searchable Memory: If Cursor encounters an obscure bug that Claude Code solved yesterday, Cursor searches directly through past tasks in fanTask and retrieves the verified fix, without blind guessing or rewrites.

What Your Workflow Looks Like: You Conduct, the AI Plays

By introducing fanTask as your coordination layer, your development dynamic transforms:

1. You retain full visibility: Through the modern fanTask web dashboard, you track project progress at a glance, review tickets awaiting approval in in_review, and mark completed work as done.
2. Your AI agents act like disciplined engineers: They no longer churn blindly on unstructured prompts. They fetch their context, claim tickets from fanTask, and log their progress in clear, structured comments.
3. Switch tools with confidence: You can move freely from the CLI to your IDE or adopt newly released AI coding models. As long as a tool speaks MCP, it plugs into your existing workflow instantly.

Build Without Fear of Chaos

Leveraging a diverse suite of AI coding tools is the greatest competitive advantage a modern developer can have — provided you have a robust coordination structure in place. Don't let tool silos and context fragmentation derail your project.

The fanTask Free plan includes 1 full project board, collaboration for up to 3 team members, and unrestricted Model Context Protocol access for all your AI assistants (Claude Code, Google Antigravity, Cursor, etc.), with all essential capabilities: reading context, searching past tasks, managing tickets, and recording decisions.

Try fanTask for free and unify all your AI agents in one place →