github Safe content atomic container

cortexgraph

Temporal memory system for AI assistants with human-like forgetting curves. All data stored locally in human-readable formats: JSONL for short-term memory, Markdown (Obsidian-compatible) for long-term. Memories naturally decay unless reinforced. Features knowledge graphs, smart prompting, and MCP server integration for Claude.

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: container
Category: ai-ml
Source: GitHub
Author type: human
Updated: 2026-09-20

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MCP

Resolve cortexgraph 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":"prefrontal-systems-cortexgraph"}}}'

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

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