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/toolprint/awesome-mcp-personasWrote 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/commands/toolprint/awesome-mcp-personas/find-mcp)<a href="https://agentmods.dev/commands/toolprint/awesome-mcp-personas/find-mcp"><img src="https://agentmods.dev/badge/commands/toolprint/awesome-mcp-personas/find-mcp/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/commands/toolprint/awesome-mcp-personas/find-mcp"><img src="https://agentmods.dev/badge/commands/toolprint/awesome-mcp-personas/find-mcp.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 | $0.00017 | $0.00208 |
| Opus 5 | $0.00009 | $0.00104 |
| Sonnet 5 | $0.00003 | $0.00042 |
| Haiku 4.5 | $0.00002 | $0.00021 |
Grade A, and why
find-mcp 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 12d 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
Find MCP Server
Discover MCP servers matching specific criteria and use cases, then research and update the server registry.
Usage
/find-mcp [purpose or criteria]
Examples
# Find database-related MCP servers
/find-mcp database integration for data analysis
# Find authentication servers
/find-mcp user authentication and authorization
# Find UI testing tools
/find-mcp browser automation and frontend testing
Workflow
- Analysis: Parse the purpose/criteria to understand requirements
- Brief Creation: Generate research brief with search strategy
- Handoff: Delegate to @mcp-researcher with the research brief
- Research & Update: Agent discovers servers and updates docs/mcp-servers.md
The @mcp-researcher agent will handle server discovery, validation, and documentation updates.
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.
- 12d ago First seen · 36 lines · 17 tokens per session scan A 179c9c09bbf4
find-mcp is a command published in the GitHub repository toolprint/awesome-mcp-personas (39 stars, last pushed 1y ago), licensed MIT. It adds 17 tokens to every session and 208 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
cost-optimize
You are a cloud cost optimization expert specializing in reducing infrastructure expenses while maintaining performance and reliability. Analyze cloud spending, identify savings opportunities, and implement cost-effective architectures across AWS, Azure, GCP, and OCI. Where provider-specific code appears below, adapt…
api-mock
You are an API mocking expert specializing in creating realistic mock services for development, testing, and demonstration purposes. Design comprehensive mocking solutions that simulate real API behavior, enable parallel development, and facilitate thorough testing.
performance-optimization
Orchestrate end-to-end application performance optimization from profiling to monitoring.
refactor-clean
You are a code refactoring expert specializing in clean code principles, SOLID design patterns, and modern software engineering best practices. Analyze and refactor the provided code to improve its quality, maintainability, and performance.
deps-audit
Audit project dependencies for vulnerabilities, outdated packages, license conflicts, and supply chain risks — then provide actionable remediation strategies.
data-driven-feature
Build features guided by data insights, A/B testing, and continuous measurement.