Cotal
The open standard for agent coordination
No outside reports on file
Cotal is experimental software with low adoption, so use it only in controlled environments with trusted agents until the project matures and proves its security.
Based on public adoption and transparency signals as of Oct 24, 2026. Our opinion, not a code audit or security guarantee.
What it can access
- Local filesNo local folder access notedLOW
- Command executionNo shell command runner notedLOW
- Network reachConnects to outside service APINOTED
- CredentialsNo API token requiredLOW
- Package sourcenpm (@cotal-ai/core)PUBLIC
Inferred from this listing’s public package details and description. Check the project’s source before installing.
Install
npx -y @cotal-ai/coreEverything known
We found nothing about this project in the sources we read (last checked 2026-10-30). That does not mean it has no problems.
0 incidents · 0 advisories · 0 news articles · 0 community threads · checked 2026-10-30
Popularity grade: B (from public signals such as stars and downloads, not a code review). Graded 2026-10-24.
Sources we read: OSV, GitHub Advisory Database, CISA Known Exploited Vulnerabilities, 44 security news feeds and our incident library. Last checked 2026-10-30.
About Cotal
Cotal is a standard framework that helps multiple AI agents coordinate and work together. It provides tools and rules so different agents can communicate, share tasks, and operate as a team instead of independently.
Who it’s for
Developers building systems where multiple AI agents need to collaborate on complex tasks. Teams creating agent-based applications that require orchestration and communication between different AI services.
Alternatives
- CrewAI: A framework for orchestrating AI agents with defined roles and tasks
- AutoGen (Microsoft): A library for building multi-agent systems with customizable communication patterns
- LangChain Agent Executor: Tool-use framework with agent coordination built into LangChain ecosystem
- Swarm (OpenAI): Lightweight agent coordination for multi-turn workflows
Setup
Check these steps against the project’s own instructions before running anything.
Install via npm:
npm install @cotal-ai/core
For Claude Desktop integration, add to claude_desktop_config.json mcpServers section following the project's README at https://github.com/Cotal-AI/Cotal (opens external site)
Why this grade
Signal-based grade (4/7 points): listed in several sources, public source code. This reflects adoption and transparency, not a code review.
Popularity and upkeep
- GitHub stars
- 369
- Weekly npm downloads
- 20.3k
- Listing last refreshed
- 2026-10-30
These are public popularity signals, not a maintenance check. Look at the repository’s commit history and open issues.
Risks to watch for
- Agent privilege escalation: If one agent gains excess permissions, it could access or control other agents' operations and data without intended boundaries
- Data leakage between agents: Poorly configured coordination could expose sensitive information passed between agents to unauthorized parties
- Malicious agent injection: An attacker could introduce a rogue agent into the coordination system to intercept or manipulate tasks and responses
- Unclear task routing: Vague or ambiguous task definitions could be exploited to redirect agents toward unintended targets or operations
- Early-stage project risks: The project shows minimal adoption (0 weekly npm downloads, low GitHub activity), meaning fewer eyes on security issues and less production testing
How to lower the risk
Least-privilege permissions
- Grant each agent only the specific permissions it needs for its role
- Review and restrict what data each agent can read or modify
Network isolation
- Run agents on isolated networks or containers when possible
- Limit which agents can communicate with external services
Monitoring
- Log all agent interactions and task routing for audit trails
- Watch for unexpected communication patterns between agents
Red flags to watch for
- Agents making requests outside their defined scope or permissions
- Unusual data volumes or types being passed between agents
- New or unverified agents joining the coordination system
Questions
How do I install Cotal?
Install Cotal with npm install @cotal-ai/core or run it directly with npx -y @cotal-ai/core. For agent integration and configuration flags, see the documentation at github.com/Cotal-AI/Cotal. Pin an exact version and pass --ignore-scripts if you want to block post-install hooks.
Are there security reports about Cotal?
No reports found for this package in our research (last checked 2026-10-30). Cotal currently holds Grade B (Some risk signals) based on public adoption and transparency signals. Key risk areas to watch include agent privilege escalation, data leakage between agents, malicious agent injection.
Is Cotal actively maintained?
Cotal has 369 GitHub stars and 20.3k weekly npm downloads. Our directory data was last refreshed on 2026-10-30. Check recent commit activity, release tags, and open issues at github.com/Cotal-AI/Cotal before pinning it in production.
What are alternatives to Cotal?
Notable alternatives to Cotal include CrewAI (A framework for orchestrating AI agents with defined roles and tasks), AutoGen (Microsoft) (A library for building multi-agent systems with customizable communication patterns), LangChain Agent Executor (Tool-use framework with agent coordination built into LangChain ecosystem), Swarm (OpenAI) (Lightweight agent coordination for multi-turn workflows). You can also compare Cotal side by side with other skills in the Related tools section on this page.
README badge and team notes
Maintain or use Cotal? Show its live grade in your GitHub README, docs site, or run a check from the terminal before you install.
GitHub README Markdown:
[](https://agentarmorhq.com/skills/cotal-ai-cotal)HTML embed:
<a href="https://agentarmorhq.com/skills/cotal-ai-cotal"><img src="https://agentarmorhq.com/api/badge/cotal-ai-cotal" alt="AgentArmorHQ Risk Grade for Cotal" height="20" /></a>Terminal check:
curl -fsSL https://agentarmorhq.com/api/cli | node --input-type=module - check "cotal-ai-cotal"Share with your security lead
Need sign-off to use Cotal? Copy this note for Slack, a ticket or a pull request.
### AgentArmorHQ Security Review Memo: Cotal
- **Listing URL:** https://agentarmorhq.com/skills/cotal-ai-cotal
- **Type:** AI agent skill
- **Risk Grade:** Grade B (Some risk signals)
- **Outside Security Advisories on File:** 0
- **Public Adoption:** 369 GitHub stars, 20.3k weekly npm downloads
#### Permission & Blast-Radius Signals
- **Local files:** No local folder access noted
- **Command execution:** No shell command runner noted
- **Network reach:** Connects to outside service API
- **Credentials:** No API token required
- **Package source:** npm (@cotal-ai/core)
#### Recommended Hardened Setup
- **Command:** `npx -y --ignore-scripts @cotal-ai/core`
- **Controls:** Pin an exact version in `.mcp.json`, scope access to a single workspace folder, and use a least-privilege read-only token where supported.
_Based on public adoption and transparency signals as of Oct 24, 2026. Our opinion, not a code audit or security guarantee._Key facts
- Type
- AI agent skill
- Publisher
- Cotal-AI
- Source code
- github.com/Cotal-AI/Cotal
- Install command
- npm install @cotal-ai/core
- Est. context load
- ~50 tokens idle · ~450 tokens when active (on-demand skill)
- Popularity
- 369 GitHub stars, 20.3k weekly npm downloads
- Last updated
- 2026-10-30
- Last graded
- 2026-10-24
Community
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