Cogmem

Name: Cogmem
Author: writerslogic

by writerslogicversion 2.7.1i★ –iRuns on your computer

Registry nameio.github.writerslogic/cogmem

Install

Overview

Description from the maker (original English)

A self-improving, verifiable memory layer for AI coding agents.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "cogmem": {
      "command": "uvx",
      "args": [
        "cogmem",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add cogmem -- uvx cogmem mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "cogmem": {
      "command": "uvx",
      "args": [
        "cogmem",
        "mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "cogmem": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "cogmem",
        "mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account writerslogic, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7246 servers in this category
Published to the registry more recently than 22% of the other 7246 servers in this category
Basic checks equal to or better than 100% of the other 7246 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Cogmem safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (2.7.1) reached the registry 4 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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by upstash

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Computer or cloud★ 64,224MITUpdated today

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Codebase Memory

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Runs on your computer★ 48,148MITUpdated 20 days ago

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Exa

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Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

cogmem

A self-improving, verifiable memory layer for AI coding agents.

A self-improving, verifiable memory layer for AI coding agents.

cogmem learns how you work across sessions so your agent gets more accurate and more autonomous over time: it stops repeating mistakes, keeps a live model of each project, and surfaces the right lesson at the right moment. Every memory is cryptographically signed and tamper-evident, so a poisoned or altered memory can be detected and rejected before it ever steers the agent.

Developed by WritersLogic — local-first recall; your memory and identity key stay on your machine (see Privacy).

Installation

From PyPI

pip install cogmem            # CLI + MCP server + verifiable-memory tools

pip install 'cogmem[recall]' # add local semantic recall (fastembed) cogmem init # wire the Claude Code hooks + build the index

pip install cogmem gives you the cogmem CLI and the MCP server (cogmem mcp, or uvx cogmem mcp on demand) — the verifiable-memory tools need only the core install. Add the [recall] extra for local semantic recall, then run cogmem init to wire the full learning loop (the SessionStart/UserPromptSubmit/Stop hooks and the index) into Claude Code. cogmem init is idempotent; re-run it any time.

Clone installer (turnkey, with the warm daemon)

The clone installer does everything pip install + cogmem init does, plus sets up the warm recall daemon (launchd/systemd) as a managed service:

git clone https://github.com/writerslogic/cogmem.git

cd cogmem ./install.sh

Or in one line:

curl -fsSL https://raw.githubusercontent.com/writerslogic/cogmem/main/install.sh | bash

install.sh is idempotent — run it again any time to upgrade in place. It sets up the code under ~/.claude/cogmem, a self-contained virtualenv with dependencies, the cogmem CLI on your PATH, the Claude Code hooks, and a warm recall daemon (a launchd agent on macOS, a systemd --user service on Linux). Requires Python 3.12+; semantic recall runs on a local model (fastembed, no external API). Pass --no-daemon or --no-hooks to skip those steps; set COGMEM_HOME to install elsewhere — the CLI, engine, and hooks all resolve it at runtime, so a non-default install keeps its memory and identity fully self-contained.

Custom Installation

Install to a different directory

Set COGMEM_HOME to place cogmem somewhere other than the default ~/.claude/cogmem:

COGMEM_HOME=/opt/cogmem ./install.sh

Or with the one-liner:

curl -fsSL https://raw.githubusercontent.com/writerslogic/cogmem/main/install.sh | COGMEM_HOME=/opt/cogmem bash

The installer copies the code, creates the virtualenv, and symlinks the CLI to ~/.local/bin/cogmem (or wherever COGMEM_BIN points).

CLI path

Set COGMEM_BIN to control where the cogmem CLI symlink is placed:

COGMEM_BIN=$HOME/.cargo/bin COGMEM_HOME=/opt/cogmem ./install.sh

If COGMEM_BIN is not on your PATH, the installer prints a warning. You can always invoke cogmem directly from $COGMEM_HOME/cogmem.

How data directories and identity keys are resolved

At runtime the CLI and engine read COGMEM_HOME from the environment. When it is unset they fall back to ~/.claude/cogmem. All runtime data lives under the vault/ subdirectory:

Path	Purpose
`$COGMEM_HOME/vault/identity/agent.key`	Ed25519 private key (agent identity, `did:key`)
`$COGMEM_HOME/vault/credentials/`	W3C Verifiable Credential storage
`$COGMEM_HOME/vault/rules/`	Layer-A (always-load) and Layer-B (recall) rules
`$COGMEM_HOME/vault/provenance/log.jsonl`	Append-only hash-chained transparency log
`$COGMEM_HOME/vault/provenance/statements/`	COSE_Sign1 SCITT signed statements
`$COGMEM_HOME/engine/.venv/`	Python virtualenv with dependencies
`$COGMEM_HOME/hooks/`	Claude Code hook scripts

The identity key is generated on first run (via cogmem status or any engine operation) and persisted at $COGMEM_HOME/vault/identity/agent.key. The corresponding did:key is derived from the Ed25519 public key. Moving or reinstalling cogmem to a new COGMEM_HOME creates a fresh identity unless you migrate the vault/ directory.

MCP client with a non-default install

The standard MCP client configuration works regardless of COGMEM_HOME because the cogmem CLI resolves the environment variable at runtime:

"mcpServers": { "cogmem": { "command": "cogmem", "args": ["mcp"] } } }

If the CLI is not on your PATH, use the full path:

"mcpServers": { "cogmem": { "command": "/opt/cogmem/cogmem", "args": ["mcp"] } } }

Or prefix with COGMEM_HOME in a shell wrapper:

"mcpServers": { "cogmem": { "command": "env", "args": ["COGMEM_HOME=/opt/cogmem", "cogmem", "mcp"] } } }

Quick Start

cogmem status           # health check, metrics, agent DID

cogmem doctor # end-to-end learning-loop health (daemon, API key, trust, backlog) cogmem recall "..." # surface relevant past lessons for a task cogmem note "..." # record a decision or finding mid-task cogmem verify # verify every memory's credential + the transparency log cogmem receipt # inclusion proof that a memory is committed in the signed log cogmem statement # COSE_Sign1 SCITT signed statement (verifiable by HMS too) cogmem trust # show the trusted agent identity (warns on a key mismatch) cogmem trust --rotate # re-anchor trust after an intentional key change cogmem review list # approve always-load rules cogmem mcp # run the MCP server (stdio) for any MCP client

MCP Integration

Run cogmem as an MCP server and connect any MCP-compatible client:

"mcpServers": { "cogmem": { "command": "cogmem", "args": ["mcp"] } } }

Eight tools are exposed: recall, note, status, verify, receipt, tree_head, progress, review_pending, plus read-only resources (the live user model and per-project state).

Claude Code Integration

install.sh wires cogmem into Claude Code automatically (idempotently merged into ~/.claude/settings.json) — no manual invocation required. Five hooks make the memory loop run in the background:

Event	Hook	What it does
`SessionStart`	`cogmem-activate.sh`	injects promoted always-load (Layer-A) rules + the self-check
`UserPromptSubmit`	`cogmem-recall.sh`	semantic Layer-B recall for the current prompt
`PreToolUse(Bash)`	`cogmem-guard.sh`	intercepts known mistakes at the tool-call boundary before they happen
`PostToolUse(Edit\	Write)`	`cogmem-context.sh`	tracks which files the session is actively editing
`Stop`	`cogmem-capture.sh`	captures the session into memory (acquisition + consolidation)

Every hook is strictly fail-open: any error, timeout, or cold daemon injects nothing and never blocks your prompt. The scripts live in ~/.claude/cogmem/hooks/; re-run install.sh (or ./install.sh --no-daemon) to refresh the wiring.

Why cogmem? -- learns from outcomes, models failure modes, verifiable memory

Chat-memory systems (Mem0, Letta, Zep) store and retrieve facts. cogmem is built for coding agents and goes further on three axes:

It learns from outcomes. A feedback loop scores whether a recalled lesson actually helped, refines rules that prove wrong, and retires ones that mislead.

It models its own failure modes. cogmem tracks where the agent tends to go wrong in your work and intercepts known mistakes at the tool-call boundary — before they happen, not afterward.

Its memory is verifiable. Each memory is a W3C Verifiable Credential signed by the agent's did:key, recorded in a tamper-evident, SCITT-style transparency log. Agent memory is an attack surface; cogmem makes it auditable and poison-resistant.

Features -- two-layer memory, outcome feedback, self-model, project state, cross-project narrative, self-regulation, verifiable credentials

Two-layer memory: always-loaded directives (scope-gated, human-approved) plus a semantic recall tail (local cross-encoder reranking, no data leaves the machine).
Outcome feedback and self-refinement: memories earn or lose trust based on whether they actually helped; contradicted rules are corrected through a safe pipeline.
Self-model and guard: a model of the agent's recurring mistakes, compiled into tripwires that intercept them at the PreToolUse boundary.
Project-state model: a living per-project state (goal, claims, open questions, blockers) that gives situational continuity and reasons across time.
Cross-project progress narrative: momentum, stalls, and dependencies across projects, surfaced as alerts.
Self-regulation: recall thresholds tuned automatically against an eval harness.
Verifiable Agent Memory: did:key identity, W3C VC-signed memories, COSE_Sign1 SCITT signed statements (byte-compatible with HMS), a hash-chained transparency log with signed Merkle tree head and RFC 6962 inclusion receipts, optional poison-resistance enforcement. See PROVENANCE.md.

Verifiable Memory -- did:key identity, W3C VC, COSE/SCITT, hash-chained log, poison-resistance

cogmem treats every stored memory as a signed artifact:

`did:key` identity: each agent gets a persistent Ed25519 identity, exposed as a W3C DID.
W3C Verifiable Credentials: every memory is signed with eddsa-jcs-2022 Data Integrity proofs.
COSE_Sign1 / SCITT signed statements: byte-identical to the envelope format used by holographic-memory and crosstalk — independently verifiable by any of the three implementations.
Hash-chained transparency log: append-only JSONL with SHA-256 chaining, a signed Merkle tree head, and RFC 6962-style inclusion receipts.
Revocation: every credential carries a W3C Bitstring Status List entry; a demoted or retired memory is revoked in a signed status-list credential.
Poison-resistance: altered or injected memories fail verification an

Only the beginning is shown; read the rest in the repo

Cogmem

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

Installation

From PyPI

Clone installer (turnkey, with the warm daemon)

Custom Installation

Install to a different directory

CLI path

How data directories and identity keys are resolved

MCP client with a non-default install

Quick Start

MCP Integration

Claude Code Integration