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 mcp/aeriondyseti/vector-memory-mcp/vector-memorygit clone --depth 1 https://github.com/aeriondyseti/vector-memory-mcpGrade A, and why
vector-memory 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 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.
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.
What it actually says
{
"vector-memory": {
"type": "stdio",
"command": "bunx",
"args": [
"-y",
"--bun",
"@aeriondyseti/vector-memory-mcp@dev",
"--plugin",
"--enable-history"
]
}
}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.
- 3d ago First seen · 13 lines scan A 7e1516831276
vector-memory is an MCP server published in the GitHub repository aeriondyseti/vector-memory-mcp (5 stars, last pushed 1mo ago), licensed MIT. Its token cost is not measured: an MCP server costs its tool schemas, not its config file. 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 mcp servers, from other repositories
haiku-rag
Local-first agentic RAG with citations - hybrid search, reranking and multimodal retrieval over your own documents, no database server required. Runs locally from the haiku-rag Python package.
compartment
Compartment - high-security, fully offline, encrypted vector memory for AI agents (MCP). Runs locally from the compartment Python package.
rag-rat
CLI and MCP entrypoint for indexing repositories into local source, graph, history, and memory evidence. Runs locally from the @rag-rat/bin npm package.
memograph
A graph-based memory system for LLMs with intelligent retrieval using knowledge graphs, hybrid search, and semantic embeddings. Runs locally from the memograph Python package. Needs 7 environment variables to run.
kb
MCP server "kb", hosted remotely at 127.0.0.1, as configured in fish827-08/rag-kb.
hubmesh
Centrality-aware GraphRAG retrieval planner — drop-in layer over any vector DB. Runs locally from the hubmesh Python package.