← council-ai.app

INDIVIDUAL MCP TOOL

council_result

Fetch the result of a council_query started with async=true.

council-ai.appnone authenticationAvailability not checked

LIVE ENDPOINT

https://mcp.council-ai.app/mcp

No auth detected

Connect to this endpoint to inspect the live schema for council_result and invoke it with your own arguments.

Indexed input schema

{}

Risk classification

Inferred read-only · medium confidence · heuristic, not a guarantee.

  • A tool name or description suggests retrieving external content.

Parent server

council-ai.app

CONNECT WITH APPROVAL

Client installation

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.council-ai]
url = "https://mcp.council-ai.app/mcp"
enabled = true
Claude Code

.mcp.json

{
  "mcpServers": {
    "council-ai": {
      "type": "http",
      "url": "https://mcp.council-ai.app/mcp"
    }
  }
}
Claude Desktop

Settings → Connectors → Add custom connector

Name: council-ai
Remote MCP URL: https://mcp.council-ai.app/mcp

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "council-ai": {
      "url": "https://mcp.council-ai.app/mcp"
    }
  }
}
Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code
{
  "servers": {
    "council-ai": {
      "type": "http",
      "url": "https://mcp.council-ai.app/mcp"
    }
  }
}
Generic MCP

Client-specific MCP configuration

{
  "name": "council-ai",
  "transport": "streamable-http",
  "url": "https://mcp.council-ai.app/mcp"
}
MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

Related tools

  • council_query — Send a prompt to a council of frontier AI models across 9 labs (Anthropic, OpenAI, Google, xAI, DeepSeek, Qwen, Mistral, Moonshot, z.
  • council_query_with_rag — Like council_query, but first retrieves the most relevant passages from the user's personal Council RAG library (uploaded PDFs, Word docs, contracts, research papers, codebases) and injects them into every model's prompt.
  • council_review — Multi-model code review.
  • library_search — Semantic search over the user's Council RAG library (uploaded PDFs, Word docs, contracts, research papers, codebases).
  • library_list — List the documents in the user's Council RAG library.
  • library_upload — Upload a document into the user's Council RAG library so future council_query_with_rag and library_search calls can retrieve it.
  • library_delete — Permanently delete a document from the user's Council RAG library — the record, every indexed chunk, AND the stored file are removed.
  • council_models — List the AI models available to the current user.