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Generate complete, tested FastMCP 3.x MCP servers from one plain-English sentence.
Generate complete, tested FastMCP 3.x MCP servers from one plain-English sentence.
mcpforge is a code generation tool with good overall security posture. Authentication is properly handled via environment variables (Anthropic, OpenAI, OpenRouter API keys), and the tool appropriately validates generated code before execution. The main concerns are broad subprocess/file write permissions inherent to a code generation tool, and some areas lacking comprehensive input validation on user-provided descriptions, but these are reasonable trade-offs for the tool's purpose. Supply chain analysis found 4 known vulnerabilities in dependencies (1 critical, 1 high severity). Package verification found 1 issue.
4 files analyzed · 12 issues found
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Set these up before or after installing:
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-saagpatel-mcpforge": {
"env": {
"ANTHROPIC_API_KEY": "your-anthropic-api-key-here"
},
"args": [
"fastmcp-builder"
],
"command": "uvx"
}
}
}From the project's GitHub README.
One English sentence in. A tested, spec-free FastMCP 3.x server out.
mcpforge turns a plain-English description into a complete FastMCP 3.x MCP server — tools, Pydantic input validation, error handling, a pytest suite, run config, and client setup docs — all wired together and ready to inspect, validate, and install. There's no MCP schema or protocol boilerplate to hand-write: the sentence is the spec. You write it; Claude writes the implementation; mcpforge runs the generated test suite and validators before you ever run it.

You need Python 3.12+, uv, and an Anthropic API key.
uv tool install fastmcp-builder # or: pip install fastmcp-builder
export ANTHROPIC_API_KEY="your_anthropic_api_key"
mcpforge generate "A weather server that returns today's forecast for a city" -o weather-server
No key yet? Try the demo.
mcpforge demoruns the real plan → generate → validate pipeline against a built-in recording and writes a complete, validated weather server — no API key, no spend. It's the fastest way to see exactly what mcpforge produces:uvx --from fastmcp-builder mcpforge demo
Bring your own key (BYOK). Generation runs on your Anthropic API key — mcpforge calls the Claude API directly and nothing is proxied through a hosted service. A single
generatemakes a few model calls (plan → server → tests), so a typical run costs roughly $0.05–$0.30 in API usage on the default model (claude-sonnet-4-6). That figure is an estimate — it scales with server complexity and your chosen model, and is not a live measurement. Everything that doesn't call the model —validate,inspect,list,doctor, andinit— is free.
That's the whole loop. mcpforge plans the tools, generates the code, then runs syntax, security, lint, import, and pytest checks against the result — so what lands in ./weather-server/ is already validated:
# weather-server/server.py (excerpt)
"""Weather forecast MCP server."""
from fastmcp import FastMCP
mcp = FastMCP("Weather")
# Illustrative lookup — describe a real source and mcpforge wires the call for you.
_FORECASTS: dict[str, dict] = {
"san francisco": {"high_c": 18, "low_c": 12, "summary": "Foggy"},
"denver": {"high_c": 24, "low_c": 9, "summary": "Clear"},
}
@mcp.tool
async def get_forecast(city: str) -> dict:
"""Return today's forecast for a city."""
key = city.strip().lower()
if key not in _FORECASTS:
raise ValueError(f"No forecast available for {city!r}")
return {"city": city, **_FORECASTS[key]}
if __name__ == "__main__":
mcp.run(transport="streamable-http")
Every generation also produces test_server.py (a real pytest suite), pyproject.toml, a README.md, and an MCP client config.json — a complete project, not a snippet. Run it with:
cd weather-server
uv run server.py # start the server (streamable-http)
uv run pytest -v # run the generated tests
mcpforge validate . # re-run the full validation suite anytime

The snippet above is an illustrative toy ("weather") for the docs. Real generations match your description — see
examples/for live generated servers (todo, file reader, database query, Slack notifier, TypeScript).
mcpforge has a sibling: mcp-audit (mcp-permission-audit on PyPI). They're two halves of one workflow — forge a server, then audit what your agents can actually touch before you trust it.
| Stage | Tool | What it does |
|---|---|---|
| Build | mcpforge | Generate a complete, tested MCP server from one sentence. |
| Audit | mcp-audit | Scan every MCP server wired into your machine and risk-score what each one can reach. |
# build
mcpforge generate "A weather server that returns today's forecast for a city" -o weather-server
# audit everything your agents can reach (read-only, no install needed)
uvx --from mcp-permission-audit mcp-audit scan --ssrf-check
mcp-audit is read-only by default — it never edits a config and reports env-var key names only, never values. Build with confidence, then verify your blast radius.
pyproject.toml, and a pytest suite generated togethermcpforge validate runs syntax, security, lint, import, and pytest checks against generated serversmcpforge update modifies an existing generated server and backs up changed files before writingmcpforge list finds mcpforge-generated projects in a workspacemcpforge inspect summarizes generated server shape, while mcpforge doctor checks local readiness--json for agent workflowsmcpforge init creates a minimal FastMCP server skeleton for local iterationmcpforge-server exposes generation, planning, validation, inspection, doctor, and discovery tools so AI assistants can build safelyThe PyPI distribution is fastmcp-builder; the installed commands are mcpforge and mcpforge-server. Beyond generate:
# See it work with no API key — generate a weather server from a built-in recording
mcpforge demo
# Generate a new MCP server
mcpforge generate "A todo list manager with create, read, update, and delete operations"
# Validate an existing generated server
mcpforge validate ./my-server
# Modify an existing generated server
mcpforge update ./my-server "Add a tool to export todos as CSV"
# Find generated servers in the current workspace
mcpforge list . --recursive
# Inspect a generated server without executing it
mcpforge inspect ./my-server
# Check local prerequisites and provider readiness
mcpforge doctor
Useful generation flags:
--dry-run displays the structured plan without writing files.--no-execute writes files but skips import and test execution.--strict treats lint errors as hard validation failures.--from-openapi FILE generates from an OpenAPI 3.x spec.--openapi-include-tag TAG, --openapi-exclude-tag TAG, --openapi-operation ID, and --openapi-limit N curate OpenAPI conversion.--language python|typescript chooses the target server language.--auth-profile none|api-key|jwt adds optional Python auth profile metadata and env docs.--middleware-profile logging|timing|rate-limit adds optional Python middleware profiles; repeat it to combine profiles.--provider anthropic|openai|openrouter selects the generation provider. openrouter is the "bring any model" path: set OPENROUTER_API_KEY and pick any OpenRouter model with --model (e.g. --model anthropic/claude-opus-4.8), including free and low-cost ones. Generation quality and structured-output support vary by model — the recommended models are Claude Opus 4.8 (xHigh) and/or GPT 5.5 (High/Extra High). OpenAI remains gated by default; set MCPFORGE_ENABLE_OPENAI_PROVIDER=1 only for opt-in smoke testing after OPENAI_API_KEY is available.Useful status flags:
mcpforge list --jsonmcpforge inspect PATH --jsonmcpforge validate PATH --jsonmcpforge doctor --jsonmcpforge version --json| Layer | Technology |
|---|---|
| Language | Python 3.12+ |
| Generation | Anthropic Claude via anthropic SDK; OpenAI provider support is gated behind hosted smokes |
| MCP framework | FastMCP 3.x |
| CLI | Click 8 |
| Templates | Jinja2 |
| Validation | Pydantic v2 |
| Output | Rich |
The generate command sends the user's description to Claude with a structured prompt that includes FastMCP 3.x idioms and a tool-schema contract. Claude returns a JSON plan (tool names, signatures, and descriptions) that mcpforge validates against a Pydantic model before rendering through Jinja2 templates into a complete project directory. The generated project is then validated with syntax checks, security scanning, ruff linting, import checks, and pytest execution. The update command reads an existing generated server, asks Claude for a targeted modification, writes backups for changed files, and validates the result.
mcpforge is published to PyPI as the fastmcp-builder distribution. The v0.3 builder lane expands mcpforge from runnable-server generation into a production integration builder with inspection, doctor checks, richer generated scaffolds, OpenAPI curation, MCP server parity, provider abstraction, remote MCP readiness docs, and live generated fixture examples for REST API, filesystem, database, authenticated OpenAPI, and TypeScript profiles. See docs/CURRENT-STATE.md, docs/ROADMAP-v0.3.md, and docs/PROVIDER-MATRIX.md.
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