About AgentForge
AgentForge is an MCP server that turns brief requests into structured prompts for coding agents, including extracted requirements and acceptance criteria. It adapts formatting to the target tool and scores prompts through its hosted engine.
Key features
- 01Extract requirements and edge cases from brief requests
- 02Adapt prompt format to the target coding tool
- 03Score quality across 12 dimensions
- 04Support multiple prompt styles
Use cases
- 01Turn a vague feature idea into an actionable task
- 02Create prompts tailored to different coding agents
- 03Check prompt quality before handing it to a coding agent
MCP support
The MCP server provides the agentforge_refine_prompt tool, which sends requests to the AgentForge API for extraction, formatting, and quality checks by the hosted engine. An API key is required.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y agentforge-mcpAGENTFORGE_API_KEYSecretYour AgentForge API key from https://agentforge.sciscale.org/account/keysAGENTFORGE_API_URLAgentForge API base URL (defaults to https://agentforge.sciscale.org)Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
1Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| style | enum | No | Execution style baked into the prompt: 'plan-first' plans before coding, 'direct-edit' makes the smallest change, 'explore-first' maps the codebase first.plan-first | direct-edit | explore-first |
| request | string | Yes | The coding task or feature request, in plain language. Rough and under-specified is fine — that is exactly what gets refined. |
| target_tool | enum | No | The AI coding agent the prompt is formatted for.claude-code | codex | cursor | aider | continue | windsurf | kimi | generic |
Details
From the project READMEagentforge-mcp
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.
Why
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:
- extracts the real requirements — the edge cases, the acceptance criteria, the things you'd have forgotten to mention;
- formats for your specific agent — Claude Code wants file:line references, Cursor wants directives, Aider wants tight context;
- quality-checks before returning — every prompt is scored across 12 dimensions before it leaves the engine.
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.
Quick start
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."
The tool — 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 vs Pro
| Free | Pro | |
|---|---|---|
| Refinements | 3 / day | Unlimited |
| Quality Engine | scored across 12 dimensions | scored + auto-refined until it passes ≥ 90 |
Or use the web app
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:

How it works
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.
Configuration
| Variable | Default | |
|---|---|---|
AGENTFORGE_API_KEY | — | Required. Your API key. |
AGENTFORGE_API_URL | https://agentforge.sciscale.org/api/v1/refine | Override the endpoint (rarely needed). |
Develop
npm install
npm run build # tsc -> dist/
node dist/index.js # runs on stdio
License
MIT — see LICENSE.
agentforge-mcp is part of AgentForge — a SciScale studio product.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.
