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.
npx agentmods add instructions/memgraph/ai-toolkit/agents-mdgit clone --depth 1 https://github.com/memgraph/ai-toolkitWhat 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 | $0.02316 | $0.02316 |
| Opus 5 | $0.01158 | $0.01158 |
| Sonnet 5 | $0.00463 | $0.00463 |
| Haiku 4.5 | $0.00232 | $0.00232 |
Grade A, and why
ai-toolkit AGENTS.md scanned grade A with 0 findings 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 2d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Guidance for coding agents working in memgraph/ai-toolkit. Keep it in sync
with the codebase — update it in the same PR as the change that makes part
of it stale.
What this repo is
Memgraph AI Toolkit — a uv workspace of independently-versioned Python
packages for building AI/agent applications on Memgraph: core DB utilities,
framework integrations (LangChain, MCP, LightRAG), a document-to-graph
pipeline, a SQL-to-graph migration agent, and Context Graph, a family of
components that turn Claude Code / Codex agent sessions into a queryable
Memgraph graph.
Repository layout
| Path | What it is |
|---|---|
memgraph-toolbox/ |
Core Memgraph client/tooling. Dependency of nearly everything else here. |
integrations/langchain-memgraph/ |
LangChain graph store, QA chain, toolkit. |
integrations/mcp-memgraph/ |
MCP server exposing Memgraph to LLMs. |
integrations/lightrag-memgraph/ |
LightRAG storage backends (KV/vector/doc-status/graph) on Memgraph. |
unstructured2graph/ |
Chunks unstructured input (files/URLs/text) and hands chunks to LightRAG for entity extraction. Outside the Context Graph family but shares its testing conventions. |
agents/sql2graph/ |
MySQL/Postgres → Memgraph migration agent. Has its own uv.lock/.python-version; run it with cd agents/sql2graph && uv run main.py. |
context-graph/ |
The Context Graph family — see below. |
scripts/dev-memgraph.sh |
Local dev lifecycle: exploration Memgraph + isolated test Memgraph for the context-graph family and unstructured2graph. |
skills/release/SKILL.md |
Release process for every PyPI/Docker-published package. |
The Context Graph family (context-graph/)
| Package | Role |
|---|---|
agent-context-graph |
Event hub. Normalizes runtime hooks / SDK activity into a shared Event Protocol and routes it to graph connectors. |
actions-graph |
Records tool calls/results/messages/subagent activity as (:Action)/(:Agent) nodes — observability, not memory. |
skills-graph |
Tracks Agent-Skills-spec (:Skill) usage per session. |
sessions-graph |
Owns (:User)/(:Session), durable (:Memory) writes/recall, and session reconciliation into (:Episode) + extracted entities. |
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.
- 2d ago First seen · 178 lines · 2,316 tokens per session scan A f629c4871565
ai-toolkit AGENTS.md is an instructions file published in the GitHub repository memgraph/ai-toolkit (112 stars, last pushed 4d ago), licensed MIT. It adds 2,316 tokens to every session, about $0.0116 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
buildNext
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
spec-kit AGENTS.md
Instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
langchain AGENTS.md
Instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.