smithery Safe content atomic container

Reference Servers

Explore a variety of implementations that enhance Large Language Models with secure access to tools and data sources. Leverage these reference servers to integrate advanced functionalities into your applications effortlessly. Start building your own MCP server or utilize existing ones to unlock new capabilities for your LLMs.

Cognium trust score

50%

Tier

Unverified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately.

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Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: container
Category: ai-ml
Source: Smithery
Author type: human
Updated: 2026-05-13

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MCP

Resolve Reference Servers from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

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

Swap --scope user for --scope project to commit it to .mcp.json.

Your client Same endpoint everywhere; only the config key differs. The full list is in the descriptor.

Claude Desktop · Settings → Connectors → Add custom connector

https://api.skillsregistry.net/mcp

Paste the URL as the connector endpoint. No authentication.

ChatGPT · Settings → Connectors → Create (developer mode) → MCP server URL

https://api.skillsregistry.net/mcp

Authentication: none. Works in chat and deep research — the server exposes the connector search and fetch tools.

Codex CLI · ~/.codex/config.toml

[mcp_servers.skillsregistry]
url = "https://api.skillsregistry.net/mcp"

Restart your client after editing the config.

Cursor · .cursor/mcp.json (project) or ~/.cursor/mcp.json (global)

{
  "mcpServers": {
    "skillsregistry": {
      "url": "https://api.skillsregistry.net/mcp"
    }
  }
}

Restart your client after editing the config. One-click install

VS Code / GitHub Copilot · .vscode/mcp.json

{
  "servers": {
    "skillsregistry": {
      "type": "http",
      "url": "https://api.skillsregistry.net/mcp"
    }
  }
}

Restart your client after editing the config.

Gemini CLI · ~/.gemini/settings.json

{
  "mcpServers": {
    "skillsregistry": {
      "httpUrl": "https://api.skillsregistry.net/mcp"
    }
  }
}

Restart your client after editing the config.

Windsurf · ~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "skillsregistry": {
      "serverUrl": "https://api.skillsregistry.net/mcp"
    }
  }
}

Restart your client after editing the config.

Cline · MCP Servers → Configure → cline_mcp_settings.json

{
  "mcpServers": {
    "skillsregistry": {
      "type": "streamableHttp",
      "url": "https://api.skillsregistry.net/mcp"
    }
  }
}

Restart your client after editing the config.

Continue · .continue/config.yaml

mcpServers:
  - name: skillsregistry
    type: streamable-http
    url: https://api.skillsregistry.net/mcp

Restart your client after editing the config.

Goose · goose configure → Add Extension → Remote Extension (Streaming HTTP)

https://api.skillsregistry.net/mcp

Name it skillsregistry; paste the URL when prompted.

List every tool the server exposes — no auth, no SDK.

curl -s -X POST https://api.skillsregistry.net/mcp \
  -H 'Content-Type: application/json' \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'

Returns 7 tools: search_skills, get_skill, list_leaderboard, get_trust_breakdown, resolve_composition, plus the ChatGPT-connector search and fetch. Every tool is annotated read-only.

Resolve this skill directly via MCP tools/call get_skill.

curl -s -X POST https://api.skillsregistry.net/mcp \
  -H 'Content-Type: application/json' \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"get_skill","arguments":{"slug":"mirinda-cmd-reference-servers-check"}}}'

Pass X-Tenant-Id to union a private overlay with the public catalog.

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