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Turn rough requests into rigorously structured prompts for any coding agent. Quality-scored to ≥90/100 across 12 dimensions, calibrated on 1,000+ real coding ca
Turn rough requests into rigorously structured prompts for any coding agent. Quality-scored to ≥90/100 across 12 dimensions, calibrated on 1,000+ real coding cases.
Stop re-explaining what you want to your AI coding agent.
Hand it one rough sentence — get back a structured, tool-tuned prompt
it can execute in one pass.

agentforge-mcp is the Model Context Protocol
server for AgentForge. One tool, one job: turn
a vague request into a sharp one.
You know the loop: you ask your coding agent for something, it misreads the half you didn't spell out, you correct it, it breaks something else, you re-explain. The fix isn't a smarter agent — it's a sharper prompt.
AgentForge does the prompt engineering for you. Give it
"add a dark mode toggle that persists" and it:
Harness engineering is having a moment — but prompt engineering matters more in the coding-agent era, not less. Tested across 1,000+ real coding cases, projects with AgentForge in the loop reached a deployable state 147% faster.
No install — it runs through npx.
1. Get an API key. Sign in at agentforge.sciscale.org, open API keys, and create one. The key is shown once — copy it.
2. Add it to your agent.
Claude Code:
claude mcp add agentforge --env AGENTFORGE_API_KEY=af_your_key -- npx -y agentforge-mcp
Cursor / Windsurf / Claude Desktop — add to your MCP config
(~/.cursor/mcp.json, ~/.codeium/windsurf/mcp_config.json, etc.):
{
"mcpServers": {
"agentforge": {
"command": "npx",
"args": ["-y", "agentforge-mcp"],
"env": { "AGENTFORGE_API_KEY": "af_your_key" }
}
}
}
3. Use it. Ask your agent naturally — "refine this with AgentForge, then build it: add a dark mode toggle that persists."
agentforge_refine_prompt| Argument | Default | |
|---|---|---|
request |
— | Your task in plain language (1–4000 chars). Rough is fine. |
target_tool |
claude-code |
claude-code, codex, cursor, aider, continue, windsurf, kimi, generic |
style |
plan-first |
plan-first, direct-edit, explore-first |
Returns the refined prompt, plus its Quality Engine score and your remaining daily usage.
| Free | Pro | |
|---|---|---|
| Refinements | 3 / day | Unlimited |
| Quality Engine | scored across 12 dimensions | scored + auto-refined until it passes ≥ 90 |
Don't want to wire up an MCP server at all? The same engine — same Quality Engine, same per-account Pro — runs right in your browser at agentforge.sciscale.org. No install, no key, no config.
Paste a request, pick your target tool, copy the prompt — generation history and advanced modes included:

agentforge-mcp is a thin client — no engine logic ships in this package. Your
request goes to the AgentForge API, the hosted engine does the extraction,
formatting, and quality-checking, and the prompt comes back. The engine keeps
improving without you ever updating this package.
| Variable | Default | |
|---|---|---|
AGENTFORGE_API_KEY |
— | Required. Your API key. |
AGENTFORGE_API_URL |
https://agentforge.sciscale.org/api/v1/refine |
Override the endpoint (rarely needed). |
npm install
npm run build # tsc -> dist/
node dist/index.js # runs on stdio
MIT — see LICENSE.
agentforge-mcp is part of AgentForge — a SciScale studio product.
Выполни в терминале:
claude mcp add agentforge-mcp -- npx Web content fetching and conversion for efficient LLM usage.
Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
автор: modelcontextprotocolProvides auto-configuration for setting up an MCP server in Spring Boot applications.
A very streamlined mcp client that supports calling and monitoring stdio/sse/streamableHttp, and can also view request responses through the /logs page. It also
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