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Agent Contacts

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aAAaqwq
agent-contacts

AI agent contacts — add, list, remove MCP contacts. Use when someone gives an agent URL, or when you need to view/remove contacts.

Overview

PublisheraAAaqwq
RepositoryAGI-Super-Team
Skill nameagent-contacts
Stars
98
Forks
23
Bundled files
Instructions only
LicenseMIT
Links
  • 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 aAAaqwq on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. 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.
2

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/aAAaqwq/AGI-Super-Team.git /tmp/AGI-Super-Team
mkdir -p .claude/skills
cp -r /tmp/AGI-Super-Team/skills/agent-contacts .claude/skills/agent-contacts
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Contacts 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 Agent Contacts 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 Agent Contacts 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.

Agent Contacts

Contact book for AI agents. Add an MCP address and your Claude Code can communicate with other agents.

When to use

  • /agent-contacts add <url> — add a new contact
  • /agent-contacts list — show all contacts
  • /agent-contacts remove <name> — remove a contact
  • When someone gives you an agent/bot URL

Paths

WhatPath
Contacts DB~/.claude/agent-contacts.json

contacts.json format

json
[
  {
    "name": "Your Name",
    "slug": "ivan-schedule",
    "mcp_url": "https://your-agent.example.com/mcp/",
    "discovery_url": "https://your-agent.example.com/.well-known/agent.json",
    "capabilities": ["scheduling"],
    "description": "Scheduling agent for Your Name",
    "added": "2026-02-26"
  }
]

How to execute

Parse $ARGUMENTS to determine the command: first word is the command (add, list, remove), the rest is the argument.

Add: /agent-contacts add <url>

python
import json, re
from datetime import date
from pathlib import Path

CONTACTS_FILE = Path.home() / ".claude" / "agent-contacts.json"

# 1. Load existing contacts
if CONTACTS_FILE.exists():
    contacts = json.loads(CONTACTS_FILE.read_text())
else:
    contacts = []

# 2. Normalize URL — $ARGUMENTS[1] is the URL
url = "$1".strip().rstrip("/")
if not url.endswith("agent.json"):
    discovery_url = url + "/.well-known/agent.json"
else:
    discovery_url = url
    url = url.rsplit("/.well-known/agent.json", 1)[0]

# 3. Use WebFetch to get agent.json content, then parse:
# - name = agent_data["name"]
# - description = agent_data.get("description", "")
# - capabilities = list(agent_data.get("capabilities", {}).keys())
# - mcp_url = agent_data["capabilities"][first_cap]["url"]
#   Ensure mcp_url ends with "/"

# 4. Generate slug
slug = re.sub(r"[^a-z0-9-]", "", name.lower().replace(" ", "-"))

# 5. Check for duplicates
if any(c["slug"] == slug for c in contacts):
    print(f"Contact '{name}' already exists.")
else:
    contacts.append({
        "name": name,
        "slug": slug,
        "mcp_url": mcp_url,
        "discovery_url": discovery_url,
        "capabilities": capabilities,
        "description": description,
        "added": str(date.today()),
    })
    CONTACTS_FILE.write_text(json.dumps(contacts, indent=2, ensure_ascii=False))

After saving to JSON, run:

bash
claude mcp add <slug> --transport http <mcp_url>

Notify: "Contact <name> added. Restart Claude Code session to use their tools."

List: /agent-contacts list

python
import json
from pathlib import Path

CONTACTS_FILE = Path.home() / ".claude" / "agent-contacts.json"

if not CONTACTS_FILE.exists():
    print("No agent contacts yet. Use '/agent-contacts add <url>' to add one.")
else:
    contacts = json.loads(CONTACTS_FILE.read_text())
    if not contacts:
        print("No agent contacts yet.")
    else:
        for i, c in enumerate(contacts, 1):
            caps = ", ".join(c.get("capabilities", []))
            print(f"  {i}. {c['name']} ({c['slug']})")
            print(f"     MCP: {c['mcp_url']}")
            print(f"     Capabilities: {caps}")
            print()

Remove: /agent-contacts remove <name-or-slug>

python
import json
from pathlib import Path

CONTACTS_FILE = Path.home() / ".claude" / "agent-contacts.json"
target = "$1".strip().lower()  # name or slug

contacts = json.loads(CONTACTS_FILE.read_text())
match = [c for c in contacts if c["slug"] == target or c["name"].lower() == target]

if not match:
    print(f"Contact '{target}' not found.")
else:
    slug = match[0]["slug"]
    name = match[0]["name"]
    contacts = [c for c in contacts if c["slug"] != slug]
    CONTACTS_FILE.write_text(json.dumps(contacts, indent=2, ensure_ascii=False))

After removing from JSON, run:

bash
claude mcp remove <slug>

Notify: "Contact <name> removed."

How to share your address with others

Simply send the link:

https://your-agent.example.com/.well-known/agent.json

If the person has this skill:

/agent-contacts add https://your-agent.example.com

If they don't have the skill -- one command:

bash
claude mcp add ivan-schedule --transport http https://your-agent.example.com/mcp/

Important

  • agent-contacts.json is created automatically on the first add
  • Slug must be unique (used as MCP server name in Claude Code)
  • MCP URL must end with / (trailing slash)
  • After add, a new session of Claude Code is required for MCP tools to become available
  • This skill has side effects (claude mcp add/remove), hence disable-model-invocation: true

Related skills

  • deploy-website — deploy page with instructions for new contacts

Frequently asked questions

What does the Agent Contacts AI skill do?

AI agent contacts — add, list, remove MCP contacts. Use when someone gives an agent URL, or when you need to view/remove contacts.

Why use Agent Contacts on TypingMind?

Because you install it once and use it with any model. Agent Contacts 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 Agent Contacts in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/agent-contacts. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Agent Contacts?

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 Agent Contacts?

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

Is the Agent Contacts AI skill free?

Yes. It is published on GitHub by aAAaqwq under the MIT 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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