mcp-memory-service AGENTS.md

A repository guide for MCP Memory Service, a service that stores information for AI assistants so they can search and reuse it later. It covers supported storage systems, setup commands, servers, dashboards, and tests.

In plain words
What is it for?
Use it when setting up the service, starting its standard-input or HTTP server, running tests, checking storage backends, or connecting it to supported AI applications.
Why use it?
It explains how to install, run, inspect, and test the memory service across its supported modes. It also helps contributors understand the project’s storage and integration choices.

Instructions file for CodexOpenCode

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/alphaplapplap/mcp-memory-service/agents-md
Clone the repo
git clone --depth 1 https://github.com/alphaplapplap/mcp-memory-service

Made for: Codex, OpenCode.

Per session 1,385 This file is loaded in full into every session.
When invoked 1,385 The same file — it is already loaded in full.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.01385 $0.01385
Opus 5 $0.00692 $0.00692
Sonnet 5 $0.00277 $0.00277
Haiku 4.5 $0.00138 $0.00138

Measured 3d ago against content hash ab2c800509c1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mcp-memory-service AGENTS.md 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 3d 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 https://localhost:8443/api/health
AGENTS.md · 179 lines

How it starts

The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

AI coding agent instructions for MCP Memory Service - a universal memory service providing semantic search and persistent storage for AI assistants.

Project Overview

MCP Memory Service implements the Model Context Protocol (MCP) to provide semantic memory capabilities for AI assistants. It supports multiple storage backends (SQLite-vec, ChromaDB, Cloudflare) and works with 13+ AI applications including Claude Desktop, VS Code, Cursor, and Continue.

Setup Commands

# Install dependencies (platform-aware)
python install.py

# Alternative: UV installation (faster)
uv sync

# Start development server
uv run memory server

# Run with inspector for debugging
npx @modelcontextprotocol/inspector uv run memory server

# Start HTTP API server (dashboard at https://localhost:8443)
uv run memory server --http --port 8443

Testing

# Run all tests
pytest tests/

# Run specific test categories
pytest tests/test_server.py          # Server tests
pytest tests/test_storage.py         # Storage backend tests
pytest tests/test_embeddings.py      # Embedding tests

# Run with coverage
pytest --cov=mcp_memory_service tests/

# Verify environment setup
python scripts/validation/verify_environment.py

# Check database health
python scripts/database/db_health_check.py

Code Style

  • Python 3.10+ with type hints everywhere
  • Async/await for all I/O operations
  • Black formatter with 88-char line length
  • Import order: stdlib, third-party, local (use isort)
  • Docstrings: Google style for all public functions
  • Error handling: Always catch specific exceptions
  • Logging: Use structured logging with appropriate levels

Project Structure

src/mcp_memory_service/
├── server.py           # Main MCP server implementation
├── mcp_server.py       # MCP protocol handler
├── storage/            # Storage backend implementations
│   ├── base.py        # Abstract base class
│   ├── sqlite_vec.py  # SQLite-vec backend (default)
│   ├── chroma.py      # ChromaDB backend
│   └── cloudflare.py  # Cloudflare D1/Vectorize backend
├── embeddings/         # Embedding model implementations
├── consolidation/      # Memory consolidation algorithms
└── web/               # FastAPI dashboard and REST API

Read the full file on GitHub · 179 lines

Changes

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.

  1. 3d ago First seen · 179 lines · 1,385 tokens per session scan A ab2c800509c1

Subscribe to this mod's changes

mcp-memory-service AGENTS.md is an instructions file published in the GitHub repository alphaplapplap/mcp-memory-service (9 stars, last pushed 11mo ago), licensed Apache-2.0. It adds 1,385 tokens to every session, about $0.0069 per session on Opus 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 2026-08-31.

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