# signallama

> signallama — fbarresi-signallama. Use this tool when you need to integrate a lightweight chat interface with your own MCP servers, solving communication and collaboration problems in development environments. It accepts input from users and servers, and outputs chat messages and data, providing a seamless interface for communication. Ideal for use cases where a simple, customizable chat solution is required, such as development teams or community servers.

Canonical page: https://skillsregistry.net/skills/fbarresi-signallama  
JSON: https://api.skillsregistry.net/v1/skills/fbarresi-signallama

## Description

lightweight chat interface designed to work seamlessly with your own MCP servers

## Trust

- **Trust score (0–1):** 0.96
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/fbarresi/signallama)

## Use it

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": "fbarresi-signallama"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/fbarresi-signallama` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/fbarresi-signallama/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