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.
git clone --depth 1 https://github.com/emergent-wisdom/understanding-graphWrote 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/mcp/emergent-wisdom/understanding-graph/ug)<a href="https://agentmods.dev/mcp/emergent-wisdom/understanding-graph/ug"><img src="https://agentmods.dev/badge/mcp/emergent-wisdom/understanding-graph/ug/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/mcp/emergent-wisdom/understanding-graph/ug"><img src="https://agentmods.dev/badge/mcp/emergent-wisdom/understanding-graph/ug.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
Grade A, and why
ug 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 6d 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
{
"ug": {
"command": "npx",
"args": [
"-y",
"[email protected]",
"mcp"
],
"env": {
"PROJECT_DIR": "./projects",
"UG_SOURCE_ROOT": "."
}
}
}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.
- 6d ago Changed 49f3581ecf8c
- 1mo ago First seen · 14 lines scan A 7cfe07d52c25
ug is an MCP server published in the GitHub repository emergent-wisdom/understanding-graph (1 stars, last pushed 6d 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 2026-08-31.
Other mcp servers, from other repositories
plexus
Typed on-prem knowledge graph for AI agents — read-only for humans, write-only for agents via MCP. Remote server at {plexus_host}.
telemem
Long-term & multimodal memory for AI agents — character isolation, video pipeline, MCP server, mem0-compatible. Runs locally from the telemem Python package. Needs 3 environment variables to run.
ori-memory
Persistent memory infrastructure for AI agents. Identity, knowledge graph, and search. Runs locally from the ori-memory npm package.
codebase-memory-mcp
MCP server "codebase-memory-mcp" as configured in suyoumo/ClawProBench. Launched with codebase-memory-mcp.
keymem
Associative memory for LLM agents — a key-graph memory layer (MCP server) that recalls by association, not just vector similarity. A graph-based alternative to vector-store agent memory. Runs locally from the keymem npm package. Needs 3 environment variables to run.
akb
Git-backed org memory for AI agents — hybrid search, tables, files & a URI graph over MCP. Runs locally from the akb-mcp npm package. Needs 2 environment variables to run.