# Connic

> Connic — co-connic-mcp. Use this tool when you need to streamline the development and deployment of AI agents, solving problems such as fragmented workflows and inefficient operation. Connic builds, tests, deploys, and operates agents, accepting inputs like agent designs and configurations, and producing outputs like functional agents and operational metrics. It is ideal for use cases where automated agent management is crucial, such as large-scale AI deployments and complex system integrations.

Canonical page: https://skillsregistry.net/skills/co-connic-mcp  
JSON: https://api.skillsregistry.net/v1/skills/co-connic-mcp

## Description

Build, test, deploy, and operate Connic agents.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-04

## Facts

- **Version:** 0.2.3
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** devops-ci
- **Updated:** 2026-09-04

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/co.connic%2Fmcp)

## Use it

MCP endpoint published by the skill: `https://mcp.connic.co/mcp`

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "co-connic-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/co-connic-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/co-connic-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt