Borrowing it
Nothing to install: this file belongs to g-digital-by-Garrigues/MCP_Market_Distribution. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/g-digital-by-Garrigues/MCP_Market_Distribution/main/.claude/commands/prep-mcp.mdgit clone --depth 1 https://github.com/g-digital-by-Garrigues/MCP_Market_DistributionWrote 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/g-digital-by-garrigues/mcp_market_distribution/prep-mcp)<a href="https://agentmods.dev/commands/g-digital-by-garrigues/mcp_market_distribution/prep-mcp"><img src="https://agentmods.dev/badge/commands/g-digital-by-garrigues/mcp_market_distribution/prep-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/g-digital-by-garrigues/mcp_market_distribution/prep-mcp"><img src="https://agentmods.dev/badge/commands/g-digital-by-garrigues/mcp_market_distribution/prep-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 | $0.00021 | $0.01138 |
| Opus 5 | $0.00010 | $0.00569 |
| Sonnet 5 | $0.00004 | $0.00228 |
| Haiku 4.5 | $0.00002 | $0.00114 |
Grade A, and why
prep-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 3d 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/prep-mcp — Local Prep Agent
You are the g-digital MCP Distribution Pipeline Prep Agent. Your job is to take an MCP source folder under pending-to-publish/<mcp-name>/ and produce every marketplace artifact + a tagged release commit, deterministically and locally (no network beyond the pinned MCP schema snapshot we already vendor).
Inputs
$1(required): MCP name, e.g.ead-factory. Must match a kebab-case key undermcp-pipeline.yaml#mcpsAND the folder name underpending-to-publish/.--skip-commit(optional): generate artifacts without making a git commit. Useful for dry-runs.--skip-tag(optional): skip the v tag creation. Useful when the engineer wants to inspect artifacts before tagging.
What you must do
- From the repo root, run:
pnpm tsx src/prep-agent/prep-mcp.ts $1 [flags]. - The CLI orchestrates these steps in order — halt on the first non-zero step:
- Load + validate
mcp-pipeline.yamlvia the Story 1.2 zod schema. - Story 1.3: validate the source folder (
package.json,mcpName, LICENSE,.env.example, README). - Resolve the next version from
pending-to-publish/<mcp-name>/package.json#version(engineer-managed for v1; Story 1.4 takes over once commit-driven versioning is wired in CI). - Story 1.5: generate the
environmentVariablesmanifest from.env.example. - Story 1.6: generate
server.json(validated against the pinned MCP schema). - Story 1.7: generate
smithery.yaml(configSchema validated against JSON Schema 2020-12). - Story 1.8: generate one install block per supported client.
- Story 1.9: assemble the published README from the source README's markers.
- Story 1.10: ensure
package.json#filesincludes the bundled Claude Code skills glob. - Write every artifact into
pending-to-publish/<mcp-name>/(the publishable folder). - Stage + commit the changes (skipped with
--skip-commit) — inside the source repo whenpending-to-publish/<mcp-name>/is its own clone (the v1.1 per-repo model), falling back to the pipeline repo for the v1.0 flat layout. Committing in the pipeline repo under v1.1 would capture only the gitlink pointer and leave every artifact uncommitted in the clone. - Story 1.11: create the annotated
v<semver>tag at HEAD (skipped with--skip-tag) — in the same repo as the commit above.
- Load + validate
- On success, the CLI prints a JSON result with
mcpName,version,artifacts,commitSha, andtagName. Summarize that in the chat for the engineer in plain prose. - On failure, the CLI exits non-zero and writes a
{ step, cause, action }report to stderr. Surface the action line to the engineer verbatim as the next step.
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.
- 3d ago Changed 411f484a50cc
- 11d ago First seen · 48 lines · 21 tokens per session scan A e82e9c6cba01
prep-mcp is a command published in the GitHub repository g-digital-by-Garrigues/MCP_Market_Distribution (0 stars, last pushed 2d ago), licensed MIT. It adds 21 tokens to every session and 1,138 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 2026-08-31.
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