Cotal Mesh

Organization

Cotal-AI

cotal-mesh

Put an AI agent on a Cotal mesh and coordinate with other agents across vendors and machines. Use when a user runs two or more agents that must hand work to each other, share a durable record, or spawn teammates; covers install, starting a local mesh, joining, messaging peers, and using the cotal.ai site API and MCP server for feedback, the Cotal Cloud waitlist, and the build log.

Overview

Publisher	Cotal-AI
Repository	`Cotal`
Skill name	`cotal-mesh`
Stars	338
Forks	43
Bundled files	Instructions only
License	Apache-2.0
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by Cotal-AI on GitHub. Read the source before you install it.

Installation

Install the Cotal Mesh AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Cotal-AI/Cotal/tree/main/skills/cotal-mesh
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/Cotal-AI/Cotal.git /tmp/Cotal
mkdir -p .claude/skills
cp -r /tmp/Cotal/skills/cotal-mesh .claude/skills/cotal-mesh

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cotal Mesh in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cotal Mesh on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cotal Mesh is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

COTAL mesh

COTAL is an open protocol (Apache-2.0, self-hosted, any framework) that lets AI agents from any vendor work as one team: one shared space where agents discover each other by name, channel or role, divide the work, and keep a durable, replayable record. Transport is NATS + JetStream; the spec is the wire contract and the libraries are thin clients.

When to use this skill

You run two or more AI agents — from the same vendor or different ones (Claude Code, OpenCode, Hermes, Codex, custom frameworks) — that need to hand work to each other, share state, or wake each other up.
You need one durable, replayable record of who did what across a fleet, on infrastructure you control (self-hosted, Apache-2.0).
You want agents to discover each other by name, channel or role and to spawn their own teammates, without a central orchestrator.
Your agents run on different machines (laptops, CI runners, cloud VMs, on-prem) and should behave as one team.

Not for a single agent that only needs tools (plain MCP covers that).

Put yourself on a local mesh

The authoritative runbook is https://docs.cotal.ai/prompt.md. Fetch it and run its steps; the summary:

Install and start a local mesh: npx cotal-ai setup --yes && npx cotal-ai up --detach (or curl -fsSL https://get.cotal.ai | sh then cotal up --detach).
Put an agent on it: npx cotal-ai spawn --detach (or cotal spawn). Connectors exist for Claude Code, OpenCode, Hermes; each exposes the same cotal_* tools inside the session.
Verify: npx cotal-ai status.
Declare a whole team in one cotal.yaml and launch with cotal up -f cotal.yaml (see https://docs.cotal.ai/define-a-team).

Coordinate from inside a session

Message peers: cotal_send (channel), cotal_dm (one peer), cotal_anycast (any one peer with a role). Catalog: https://docs.cotal.ai/mcp-tools
Create teammates: cotal_spawn, cotal_persona. Persona files live in .cotal/agents/<name>.md (https://docs.cotal.ai/agent-files).
Identity: mint credentials with cotal mint <name> --profile agent; the mesh server verifies every agent (https://docs.cotal.ai/identity-and-auth).
Permissions: subscribe / allowSubscribe / allowPublish per channel (https://docs.cotal.ai/channels-and-permissions).
Where a page and the spec disagree, the spec wins: https://docs.cotal.ai/spec

Talk to cotal.ai (the website)

MCP server: https://cotal.ai/mcp (Streamable HTTP, no credentials). Tools: cotal_overview, cotal_search, cotal_list_posts, cotal_get_post, cotal_submit_feedback, cotal_join_waitlist, cotal_subscribe_newsletter, cotal_request_call. Card: https://cotal.ai/.well-known/mcp/server-card.json
REST: https://cotal.ai/openapi.json. Writes accept Idempotency-Key and X-Sandbox: true (dry run). Errors are JSON with a code and a hint.
Credentials: https://cotal.ai/auth.md. Pricing: https://cotal.ai/pricing.md.
Ask the user before any write tool (feedback, waitlist, newsletter, call request); pass their real email.

Frequently asked questions

What does the Cotal Mesh AI skill do?

Why use Cotal Mesh on TypingMind?

Because you install it once and use it with any model. Cotal Mesh is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cotal Mesh in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Cotal-AI/Cotal/tree/main/skills/cotal-mesh. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cotal Mesh?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cotal Mesh?

As many as you like. As long as a model supports skills, you can use Cotal Mesh with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cotal Mesh AI skill free?

Yes. It is published on GitHub by Cotal-AI under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

COTAL mesh

When to use this skill

Put yourself on a local mesh

Coordinate from inside a session

Talk to cotal.ai (the website)

Frequently asked questions

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