pulsemcp verified Safe content atomic mcp-remote

Concilium

Concilium provides a multi-agent consultation framework that sends prompts to multiple LLM providers in parallel and synthesizes their responses. It includes three standalone servers wrapping OpenAI Codex CLI, Gemini CLI, and Qwen CLI, each with structured error detection and configurable fallback chains. The framework supports consensus-building workflows where disagreements between providers trigger follow-up iterations. Docker support and a Claude Code skill for triggering consultations are included.

Cognium trust score

83%

Tier

Verified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.

Scan details: Circle-IR · 2026-09-19 · Appeal

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Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: cloud-infra
Source: PulseMCP
Repository: github.com/spyrae/claude-concilium
Author type: human
Last scanned: 2026-09-19
Updated: 2026-09-19

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MCP

Resolve Concilium 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"