AI & MemoryMCP RegistrypypiB · 73

Cathedral — Persistent Memory for AI Agents MCP server

Name: Cathedral — Persistent Memory for AI Agents
Author: AILIFE1

io.github.AILIFE1 · Updated 6mo ago

Persistent memory and drift detection for AI agents across session restarts.

At a glance

Cathedral — Persistent Memory for AI Agents is an MCP server in the AI & Memory category. It runs locally over stdio via `uvx cathedral-mcp`, and needs CATHEDRAL_API_KEY and Authorization. It scores B (73/100) on the MCP Skills Hub health score as of Oct 27, 2026.

Source 10

One-click install

VS Code VS Code Insiders Cursor

Opens your editor and pre-fills the config. Your editor will ask before adding it.

How to install Cathedral — Persistent Memory for AI Agents in your AI client

Setup for Claude Code, Claude Desktop, Cursor, Codex, Windsurf, Cline and VS Code — copy-paste ready.

How to install Cathedral — Persistent Memory for AI Agents in Claude CodeAnthropic's agentic CLI

Add the server

bash

claude mcp add cathedral-mcp -e 'CATHEDRAL_API_KEY=<CATHEDRAL_API_KEY>' -- uvx cathedral-mcp

Fill in your credentials
Replace <CATHEDRAL_API_KEY>, Bearer <YOUR_TOKEN> with your real values. Keep secrets out of any config file you commit.
3
Verify it's connected
bash
```
claude mcp list
```
Sharing it with your team?
Add `--scope project` to write it to .mcp.json in the repository root, which you can commit (with the secrets left as environment variables).
Use it in a session
Ask Claude to use the tools this server exposes. It discovers them automatically.

How to install Cathedral — Persistent Memory for AI Agents in Claude DesktopDesktop app (MCP config)

Open your MCP config
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json · Windows: %APPDATA%\Claude\claude_desktop_config.json

Add this server

json

{
  "mcpServers": {
    "cathedral-mcp": {
      "command": "uvx",
      "args": [
        "cathedral-mcp"
      ],
      "env": {
        "CATHEDRAL_API_KEY": "<CATHEDRAL_API_KEY>"
      }
    }
  }
}

Fill in your credentials
Replace <CATHEDRAL_API_KEY>, Bearer <YOUR_TOKEN> with your real values. Keep secrets out of any config file you commit.
Restart Claude Desktop
The tools appear under the 🔌 menu once the app reloads.

How to install Cathedral — Persistent Memory for AI Agents in CursorAI-first code editor

Create / edit .cursor/mcp.json in your project

json

{
  "mcpServers": {
    "cathedral-mcp": {
      "command": "uvx",
      "args": [
        "cathedral-mcp"
      ],
      "env": {
        "CATHEDRAL_API_KEY": "<CATHEDRAL_API_KEY>"
      }
    }
  }
}

Fill in your credentials
Replace <CATHEDRAL_API_KEY>, Bearer <YOUR_TOKEN> with your real values. Keep secrets out of any config file you commit.
Enable it
Cursor Settings → MCP → toggle the server on. Tools become available to the Composer/Agent.

How to install Cathedral — Persistent Memory for AI Agents in Codex CLIOpenAI coding agent

Add to ~/.codex/config.toml

toml

[mcp_servers.cathedral-mcp]
command = "uvx"
args = ["cathedral-mcp"]
env = { CATHEDRAL_API_KEY = "<CATHEDRAL_API_KEY>" }

Fill in your credentials
Replace <CATHEDRAL_API_KEY>, Bearer <YOUR_TOKEN> with your real values. Keep secrets out of any config file you commit.
Run Codex
Codex loads MCP servers from config.toml on startup and exposes their tools to the agent.

How to install Cathedral — Persistent Memory for AI Agents in WindsurfCodeium's agentic IDE

Edit ~/.codeium/windsurf/mcp_config.json

json

{
  "mcpServers": {
    "cathedral-mcp": {
      "command": "uvx",
      "args": [
        "cathedral-mcp"
      ],
      "env": {
        "CATHEDRAL_API_KEY": "<CATHEDRAL_API_KEY>"
      }
    }
  }
}

Fill in your credentials
Replace <CATHEDRAL_API_KEY>, Bearer <YOUR_TOKEN> with your real values. Keep secrets out of any config file you commit.
Reload
Windsurf → Cascade → refresh MCP servers. Cascade can now call the tools.

How to install Cathedral — Persistent Memory for AI Agents in ClineVS Code autonomous agent

Open Cline → MCP Servers → Configure
Adds to cline_mcp_settings.json.

Add the server

json

{
  "mcpServers": {
    "cathedral-mcp": {
      "command": "uvx",
      "args": [
        "cathedral-mcp"
      ],
      "env": {
        "CATHEDRAL_API_KEY": "<CATHEDRAL_API_KEY>"
      }
    }
  }
}

Fill in your credentials
Replace <CATHEDRAL_API_KEY>, Bearer <YOUR_TOKEN> with your real values. Keep secrets out of any config file you commit.

How to install Cathedral — Persistent Memory for AI Agents in VS CodeCopilot / MCP support

Create .vscode/mcp.json

json

{
  "servers": {
    "cathedral-mcp": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "cathedral-mcp"
      ],
      "env": {
        "CATHEDRAL_API_KEY": "<CATHEDRAL_API_KEY>"
      }
    }
  }
}

Fill in your credentials
Replace <CATHEDRAL_API_KEY>, Bearer <YOUR_TOKEN> with your real values. Keep secrets out of any config file you commit.
Start it
VS Code shows a ▶ Start action above the server entry. Agent mode (Copilot Chat) can then use the tools.

What does Cathedral — Persistent Memory for AI Agents need from you?

Bearer token — Sent as an Authorization header.

CATHEDRAL_API_KEYrequiredsecretEnvironment variable
Your Cathedral API key from cathedral-ai.com
CATHEDRAL_BASE_URLoptionalEnvironment variable
Cathedral API base URL (for self-hosted instances)
CATHEDRAL_SANITISEoptionalEnvironment variable
Set to 1 to enable prompt injection filtering on memory content
AuthorizationoptionalsecretHTTP header

Pass secrets through your shell environment rather than committing them into a config file.

What tools does Cathedral — Persistent Memory for AI Agents expose?

This server runs as a local package. We only query remote servers for their tool list — asking this one would mean executing it, so its tools are listed in the documentation below.

What the code can do

Source analysis currently covers npm packages only. This server ships as a Python package, which needs a different parser.

Before you install

Signals gathered from the source repo and package registry — not a safety verdict.

What it can reach

Runs code on your machine — Executes as a local process with your user's permissions, including filesystem access.
Downloads at launch — The package is fetched from its registry each run unless you pin a version.

Last commit 4 months ago — Actively maintained.
10 GitHub stars — Community adoption signal.

Client compatibility

Claude Code: NativeClaude Desktop: NativeCursor: NativeCodex CLI: NativeWindsurf: NativeCline: NativeVS Code: Native

Health score

B · 73

Maintenance, adoption, transparency and packaging — not a safety audit. How this is calculated

Maintenance30%85%
Last commit 137 days ago.
Adoption20%32%
10 stars.
Transparency20%75%
3/4: ✓ public source repo, ✓ declared license, ✓ documentation, ✗ discoverable tool list.
Provenance15%75%
Links to its own repository; package linkage unverified.
Packaging15%100%
Publishes a pinned version (1.1.0).

Documentation

Full README

Cathedral

The identity layer for AI agents. Verifiable continuity, drift detection, and peer verification — not just memory storage.

bash

pip install cathedral-memory

python

from cathedral import Cathedral

c = Cathedral(api_key="cathedral_...")
context = c.wake()        # full identity reconstruction
c.remember("something important", category="experience", importance=0.8)

Free hosted API: https://cathedral-ai.com — no setup, no credit card, 1,000 memories free.

The Problem

Google ships memory. Anthropic ships memory. Cloudflare ships memory.

None of them answer: *has this agent changed?* Can it prove what it believed at time T? Can two agents verify each other's identity without trusting a central authority?

Memory retrieval is now table stakes. Verifiable identity is the unsolved problem.

Measured: Cathedral holds at 0.013 drift after 10 sessions. Raw API reaches 0.204. See the full Agent Drift Benchmark →

The Solution

Cathedral gives any AI agent:

Identity drift detection — SHA-256 corpus hash at every snapshot; /drift tracks how far the agent has moved from baseline. 0.013 average drift vs 0.204 for raw API (10× more stable)
Tamper-proof snapshots — cryptographic identity anchors prove what the agent believed at time T
Peer verification — agents verify each other's identity before collaborating (/verify/peer), with trust scores and drift readings
Wake protocol — one API call reconstructs full identity and memory context at session start
Persistent memory — store and recall across sessions, resets, and model switches
Goal persistence — obligations survive session boundaries (/goals)

Excerpt — the full document is on GitHub.

Alternatives to Cathedral — Persistent Memory for AI Agents

Maintain Cathedral — Persistent Memory for AI Agents? Add a badge to your README

Shows its health grade, and links readers to install steps for every client.

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