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 agentmods add commands/myeolinmalchi/mcp2cli/convertgit clone --depth 1 https://github.com/myeolinmalchi/mcp2cliWhat 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 | $0.00010 | $0.00320 |
| Opus 5 | $0.00005 | $0.00160 |
| Sonnet 5 | $0.00002 | $0.00064 |
| Haiku 4.5 | $0.00001 | $0.00032 |
Grade A, and why
convert 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 yesterday.
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
/convert - MCP to CLI Conversion
Convert an MCP server to a token-efficient CLI tool.
Usage
/convert <path-to-mcp-server>
Instructions
When the user runs /convert, execute these phases in order:
Phase 1 — Analyze (uses mcp-analyze skill)
- If the path is a GitHub URL, clone the repository first
- Read the MCP server's entry point and package manifest
- Extract all tool definitions, parameters, and output formats
- Classify the server pattern and assess conversion feasibility
- Present the analysis table and ask the user to confirm before proceeding
Phase 2 — Generate CLI (uses mcp-codegen skill)
- Design the CLI command structure based on the analysis
- Generate TypeScript CLI code using the appropriate tier template
- If the source is Python, refer to
mcp-codegen'sreferences/porting-cheatsheet.mdfor translation patterns
Phase 3 — Generate SKILL.md (uses skill-author skill)
- Generate a SKILL.md for the new CLI tool
- Follow the skill template and rules
Phase 4 — Validate
- Run each CLI command and verify output
- Verify the SKILL.md is correct and complete
If no path is provided, ask the user for the path to the MCP server they want to convert.
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.
- yesterday First seen · 41 lines · 10 tokens per session scan A d0b363a9a0cb
convert is a command published in the GitHub repository myeolinmalchi/mcp2cli (4 stars, last pushed 5mo ago), licensed MIT. It adds 10 tokens to every session and 320 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.