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 miticojo/ge-app-mcp --skill enterprise-contextgit clone --depth 1 https://github.com/miticojo/ge-app-mcpWrote 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/miticojo/ge-app-mcp/enterprise-context)<a href="https://agentmods.dev/skills/miticojo/ge-app-mcp/enterprise-context"><img src="https://agentmods.dev/badge/skills/miticojo/ge-app-mcp/enterprise-context/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/miticojo/ge-app-mcp/enterprise-context"><img src="https://agentmods.dev/badge/skills/miticojo/ge-app-mcp/enterprise-context.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 | $0.00061 | $0.00464 |
| Opus 5.5 | $0.00024 | $0.00186 |
| Sonnet 5.5 | $0.00012 | $0.00093 |
| Haiku 4.5 | $0.00006 | $0.00046 |
Grade A, and why
enterprise-context 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 13d 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
Enterprise Context Retriever
Never guess about proprietary systems, policies or customers. Retrieve, then answer with sources.
Rules
- Search before answering when the information is not already in your context.
- Choose the scope:
engine_id(an app) searches every source connected to it (Drive, SharePoint, Jira, connectors...). Prefer it for open questions.datastore_idtargets one source. Prefer it when the user names a source or you need precision.
- Pick the tool:
gemini_enterprise_askfor a direct question: returns a grounded answer, references and a grounding score. For follow-ups, passsession: "new"the first time and then the returned session name.gemini_enterprise_searchto explore or list documents. Narrow withfilter(e.g.category: ANY("policy")),order_by,relevance_threshold; page withpage_token. For plain retrieval on a single data store,search_addon_speccan turn off generative add-ons to reduce cost.
- Read the full document with
gemini_enterprise_get_documentwhen a snippet is not enough. - Cite sources: list title and link of every document you used. If the grounding score is low or nothing relevant is found, say so instead of filling gaps.
- Respect access: results reflect what the current user may see. Do not try other scopes or identities to get around missing results.
Scope
These tools need the search scope. If a tool returns "Access Denied", ask the operator to add
search to MCP_SCOPES.
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.
- 13d ago Changed · +13 lines · +30 tokens per session 76816dcd7932
- 2mo ago First seen · 23 lines · 31 tokens per session scan A 7bbb9e7f87a5
enterprise-context is a skill published in the GitHub repository miticojo/ge-app-mcp (0 stars, last pushed 13d ago), licensed Apache-2.0. It adds 61 tokens to every session and 464 once invoked, about $0.0002 per session on Opus 5.5. 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.
enterprise-context compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| enterprise-contextmiticojo/ge-app-mcp | Skill | 0 | 13d ago | Apache-2.0 | A | 61 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 4d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |