← e2cm2.org

INDIVIDUAL MCP TOOL

get_knowledge_graph

Return the E² = CM² concept graph (nodes, edges, or triples) linking Architecture, Research, Docs, Entities, and Principles.

e2cm2.orgnone authenticationAvailability not checked

LIVE ENDPOINT

https://e2cm2.org/mcp

No auth detected

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

Indexed input schema

{}

Risk classification

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

  • No write-capable action terms were found; this is not proof that invocation has no side effects.

Parent server

e2cm2.org

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.e2cm2-mcp]
url = "https://e2cm2.org/mcp"
enabled = true
Claude Code

.mcp.json

{
  "mcpServers": {
    "e2cm2-mcp": {
      "type": "http",
      "url": "https://e2cm2.org/mcp"
    }
  }
}
Claude Desktop

Settings → Connectors → Add custom connector

Name: e2cm2-mcp
Remote MCP URL: https://e2cm2.org/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": {
    "e2cm2-mcp": {
      "url": "https://e2cm2.org/mcp"
    }
  }
}
Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code
{
  "servers": {
    "e2cm2-mcp": {
      "type": "http",
      "url": "https://e2cm2.org/mcp"
    }
  }
}
Generic MCP

Client-specific MCP configuration

{
  "name": "e2cm2-mcp",
  "transport": "streamable-http",
  "url": "https://e2cm2.org/mcp"
}
MCP Inspector

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

Related tools

  • about_project — Return the project's core context: axiom, organization, primary URLs, and AI entry points.
  • list_routes — List every public URL on e2cm2.org with a short description — the map of the site.
  • get_ontology — Return the machine-readable ontology (node kinds, predicates, categories, provenance), the canonical vocabulary, or the project timeline.
  • get_resonance_manifest — Fetch the machine-readable resonance JSON-LD for the ambient composition 'Between Mathematics and Watermelon' — symbolic layer, architectural purpose, and audio features.