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/paladini/mcp-meWrote 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/rules/paladini/mcp-me/use-profile)<a href="https://agentmods.dev/rules/paladini/mcp-me/use-profile"><img src="https://agentmods.dev/badge/rules/paladini/mcp-me/use-profile/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/rules/paladini/mcp-me/use-profile"><img src="https://agentmods.dev/badge/rules/paladini/mcp-me/use-profile.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 | $0.00394 | $0.00394 |
| Opus 5.5 | $0.00158 | $0.00158 |
| Sonnet 5.5 | $0.00079 | $0.00079 |
| Haiku 4.5 | $0.00039 | $0.00039 |
Grade A, and why
use-profile 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 1mo 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
You have access to an MCP server called me that exposes the user's personal profile.
Always use ask_about_me or read the MCP resources below before answering any request that could benefit from knowing who the user is — writing, code review, documentation, career questions, open-source contributions, etc.
Available MCP resources
| Resource | Contains |
|---|---|
me://identity |
Name, bio, location, contact, social links |
me://career |
Work history, job titles, companies |
me://skills |
Programming languages, tools, proficiency levels |
me://projects |
Open-source repos, articles (with full text), books, npm packages |
me://interests |
Hobbies, topics of interest |
me://personality |
Traits, values, work style |
me://goals |
Short and long-term goals |
me://faq |
Pre-answered facts about the user |
When to proactively load the profile
- Writing or editing any text (articles, READMEs, cover letters, bios)
- Answering questions about skills, experience, or projects
- Generating code in a language or framework the user uses
- Recommending tools, libraries, or approaches
- Any task where knowing the user's background would improve the answer
The ask_about_me tool
Use this tool for natural-language questions. Example invocations:
ask_about_me("What open-source projects has this person published?")ask_about_me("What articles has this person written? Include full content.")ask_about_me("What are this person's strongest programming languages?")ask_about_me("What are this person's career goals?")
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.
- 1mo ago First seen · 39 lines · 394 tokens per session scan A 634007926c5d
use-profile is a cursor rule published in the GitHub repository paladini/mcp-me (21 stars, last pushed 2mo ago), licensed MIT. It adds 394 tokens to every session, about $0.0016 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 2026-08-30.
Other cursor rules, from other repositories
search-routing
Smart Search Routing — always use QMD semantic search when available, never bypass with grep for vault content.
swamr-obsidian-brain
Swamr Obsidian Brain — persistent knowledge base that agents read from and write to across phases. Prevents context loss by maintaining architecture decisions, task outputs, learned patterns, and project knowledge in an Obsidian vault. Every agent MUST read relevant notes before starting and write a summary note when…
cursor
Cursor rule "cursor" from nitingupta220/riperflow, covering riperflow σ and ω₁=🔍r→ℙ(ω₁)→research.
shared-agents-knowledge
Shared agents skills and learnings — automatic sync, retrieve, capture.
haive-memories
Hivelore shared memories & block sensors (auto-generated).
haive-mcp-required
Require Hivelore MCP (getbriefing / memrelevantto) before substantive repo edits.