Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/sopaco/cortex-memnpx agentmods add skills/sopaco/cortex-mem/skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sopaco/cortex-mem/skill)<a href="https://agentmods.dev/skills/sopaco/cortex-mem/skill"><img src="https://agentmods.dev/badge/skills/sopaco/cortex-mem/skill/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sopaco/cortex-mem/skill"><img src="https://agentmods.dev/badge/skills/sopaco/cortex-mem/skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 72 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Data Exfiltration · line 83 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 91 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 445 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 450 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium MCP Rug Pull · line 109 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00072 | $0.02911 |
| Opus 5.5 | $0.00029 | $0.01164 |
| Sonnet 5.5 | $0.00014 | $0.00582 |
| Haiku 4.5 | $0.00007 | $0.00291 |
Grade A, and why
cortex-mem-mcp scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl http://localhost:6333 How it starts
The opening of the file, as written. The whole thing — 459 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cortex Memory MCP Skill
This skill enables persistent memory capabilities for AI agents, allowing them to store, search, and recall information across sessions using semantic retrieval.
Prerequisites Check
Before configuring this skill, verify if cortex-mem-mcp is available in your system:
# Check if cortex-mem-mcp is in PATH
which cortex-mem-mcp || where cortex-mem-mcp # Linux/macOS || Windows
If the command returns a path, the binary is already installed. If not, proceed to the installation section below.
Installation
Option 1: Install from crates.io (Recommended)
cargo install cortex-mem-mcp
After installation, verify:
cortex-mem-mcp --version
Option 2: Build from Source
# Clone the repository
git clone https://github.com/sopaco/cortex-mem.git
cd cortex-mem
# Build the release binary
cargo build --release --bin cortex-mem-mcp
# The binary will be at:
# ./target/release/cortex-mem-mcp (Linux/macOS)
# .\target\release\cortex-mem-mcp.exe (Windows)
Option 3: Download Pre-built Binary
Download the latest release from GitHub:
- GitHub Releases: https://github.com/sopaco/cortex-mem/releases
Choose the appropriate binary for your platform:
cortex-mem-mcp-linux-x86_64(Linux x64)cortex-mem-mcp-darwin-arm64(macOS Apple Silicon)cortex-mem-mcp-darwin-x86_64(macOS Intel)cortex-mem-mcp-windows-x86_64.exe(Windows x64)
Configuration
Step 1: Create Configuration File
Create a config.toml file (e.g., ~/.config/cortex-mem/config.toml):
[cortex]
# Data directory for storing memories
data_dir = "~/.cortex-data"
[llm]
# LLM API configuration
api_base_url = "https://api.openai.com/v1"
api_key = "your-api-key"
model_efficient = "gpt-5-mini"
temperature = 0.1
max_tokens = 65536
[embedding]
# Embedding configuration
api_base_url = "https://api.openai.com/v1"
api_key = "your-embedding-api-key"
model_name = "text-embedding-3-small"
batch_size = 10
timeout_secs = 30
[qdrant]
# Vector database configuration
url = "http://localhost:6334"
collection_name = "cortex_memories"
embedding_dim = 1536
timeout_secs = 30
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 459 lines · 72 tokens per session scan A 2a2ae96ac8d6
cortex-mem-mcp is a skill published in the GitHub repository sopaco/cortex-mem (314 stars, last pushed 2mo ago), licensed MIT. It adds 72 tokens to every session and 2,911 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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