smithery Safe content atomic mcp-remote

Pelaris

AI fitness coaching through any MCP-compatible AI assistant. 21 tools for personalised training programs, workout logging, benchmark tracking, goal management, and coaching insights across strength, running, swimming, cycling, triathlon, CrossFit, and general fitness. Supports science-based methodologies including 5/3/1, Pfitzinger, polarised training, and more. OAuth 2.0 authentication - connect and start training. [Documentation](https://pelaris.io/integrations) · [Website](https://pelaris.io)

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.

View full trust & usage report →

Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: monitoring
Source: Smithery
Author type: human
Updated: 2026-05-13

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MCP

Resolve Pelaris 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"