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 skills add Space-C0wboy/OpenCTI-MCP-Server --skill opencti-usagegit clone --depth 1 https://github.com/Space-C0wboy/OpenCTI-MCP-ServerWrote 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/space-c0wboy/opencti-mcp-server/opencti-usage)<a href="https://agentmods.dev/skills/space-c0wboy/opencti-mcp-server/opencti-usage"><img src="https://agentmods.dev/badge/skills/space-c0wboy/opencti-mcp-server/opencti-usage/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/space-c0wboy/opencti-mcp-server/opencti-usage"><img src="https://agentmods.dev/badge/skills/space-c0wboy/opencti-mcp-server/opencti-usage.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00091 | $0.01209 |
| Opus 5 | $0.00046 | $0.00605 |
| Sonnet 5 | $0.00018 | $0.00242 |
| Haiku 4.5 | $0.00009 | $0.00121 |
Grade A, and why
opencti-usage 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 8d 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenCTI Usage
Overview
OpenCTI is a threat-intelligence platform built around a single knowledge
graph: everything it knows is expressed as STIX 2.1 objects (entities) and
the relationships between them. Containers (Reports, Groupings, Cases,
Incidents) group related entities and relationships into a citable, shareable
"story." Markings (TLP and friends) segregate who can see what, on top of
group/role-based access. Connectors are the independent processes that
ingest, enrich, and export data into and out of that graph. Almost everything
you do through the opencti MCP tools is either reading a slice of this
graph or adding/editing nodes and edges in it.
Concept map
- Observables vs Indicators — an Observable is a raw fact with no built-in judgment (an IP, a hash); an Indicator is the SDO that adds detection intent (a pattern, a validity window) and is usually "based on" one or more observables.
- Relationships — typed, directional edges (
from→to) such asuses,indicates,targets, each carrying its own confidence, timestamps, and markings — independent of the confidence on the entities they connect. - Containers / Reports — Reports, Groupings, Cases, and Incidents bundle
entities, observables, and relationships via
object_refsinto one citable unit with provenance back to a source. - Markings / TLP — marking definitions (TLP:CLEAR…TLP:RED, PAP, etc.) drive data segregation: only users authorized for a marking can see the objects carrying it.
- Confidence / scoring — confidence (0-100) rates the credibility of information itself (on entities and on relationships); score rates how dangerous an indicator/observable currently is; reliability rates the source — three distinct axes.
- Connectors / enrichment — independent processes (ingestion, enrichment,
internal-import/export) that move data into, around, and out of the
platform;
entity_ask_enrichmenttriggers one on demand for a given entity.
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/admin-connectors.md 4.4 KB
- references/api-and-graphql.md 3.2 KB
- references/confidence-and-scoring.md 5.0 KB
- references/containers.md 7.2 KB
- references/data-model.md 6.5 KB
- references/entities.md 7.8 KB
- references/indicators-vs-observables.md 7.4 KB
- references/markings-and-tlp.md 3.6 KB
- references/mcp-tool-map.md 3.7 KB
- references/rbac-and-orgs.md 6.5 KB
- references/relationships.md 5.9 KB
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.
- 8d ago First seen · 94 lines · 91 tokens per session scan A 060c47fab19f
opencti-usage is a skill published in the GitHub repository Space-C0wboy/OpenCTI-MCP-Server (0 stars, last pushed 1mo ago), licensed MIT. It adds 91 tokens to every session and 1,209 once invoked, about $0.0005 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 2026-08-31.
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